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M. M. Dobrolinska, R. A. Jukema, S. G. M. van Velzen, P. A. van Diemen, M. J. W. Greuter, N. H. J. Prakken, N. R. van der Werf, P. G. Raijmakers, R. H. J. A. Slart, P. Knaapen, I. Isgum, I. Danad, "The prognostic value of visual and automatic coronary calcium scoring from low-dose computed tomography-[¹⁵O]-water positron emission tomography", European Heart Journal - Cardiovascular Imaging, 2024.Y.Koop, F. Atsma, M. C.T. Batenburg, H. Meijer, F. van der Leij, R. Gal, S. G.M. van Velzen, I. Išgum, H. Vermeulen, A. H.E.M. Maas, S. El Messaoudi & H. M. Verkooijen , "Competing risk analysis of cardiovascular disease risk in breast cancer patients receiving a radiation boost", Cardio-Oncology, 2024; 10 (1): 7.
L. D. Van Harten, J. Stoker; I. Išgum, "Robust deformable image registration using cycle-consistent implicit representations", IEEE Transactions on Medical Imaging, 2024; 43 (2): 784-793.
S. S. Płotka, M. K. Grzeszczyk, P. I. Szenejko, K. Żebrowska, N. A Szymecka-Samaha, T. Łęgowik, M. A Lipa, K. Kosińska-Kaczyńska, R. Brawura-Biskupski-Samaha, I. Išgum, C. I. Sánchez, A. Sitek, "Deep learning for estimation of fetal weight throughout the pregnancy from fetal abdominal ultrasound", American journal of obstetrics & gynecology MFM, 2023; 5 (12): 101182.
M. Z. H. Kolk, S. Ruipérez-Campillo, L. Alvarez-Florez, B. Deb, E. J. Bekkers, C. P. Allaart, A. C. J. Lingen, P. Clopton, I. Isgum, A. A. M. Wilde, R. E. Knops, S. M. Narayan, F. V. Y. Tjong, "Dynamic prediction of malignant ventricular arrhythmias using neural networks in patients with an implantable cardioverter-defibrillator", eBioMedicine, 2023; 99 (104937): 104937.
R. L. M. Van Herten, N. Hampe, R. A. P. Takx, K. J. Franssen, Y. Wang, D. Suchá, J. P. Henriques, T. Leiner, R. N. Planken, I. Išgum, "Automatic Coronary Artery Plaque Quantification and CAD-RADS Prediction using Mesh Priors", IEEE Transactions on Medical Imaging, 2023.
S. Płotka, M. K. Grzeszczyk, R. Brawura-Biskupski-Samaha, P. Gutaj, M. Lipa, T. Trzciński, I. Išgum, C. I. Sánchez, A. Sitek, "Fetal birth weight prediction using biometry multimodal data acquired less than 24 h before delivery", Computers in Biology and Medicine, 2023 (107602).
B. D. de Vos, G. E. Jansen, I. Išgum, "Stochastic co-teaching for training neural networks with unknown levels of label noise", Scientific Reports, 2023; 13 (16875).
M. Kavousi, M. M. Bos, H. J. Barnes, C. L. L. Cardenas, D. Wong, ..., I. Išgum, ..., S. W. van der Laan, C. L. Miller, "Multi-ancestry genome-wide study identifies effector genes and druggable pathways for coronary artery calcification", Nature Genetics, 2023.
M. Z. H. Kolk, S. Ruipérez-Campillo, B. Deb, E. J. Bekkers, C. P. Allaart, A. J. Rogers, A. C. J. Lingen, L. Alvarez-Florez, I. Isgum, B. D De Vos, P. Clopton, A. A. M. Wilde, R. E. Knops, S. M. Narayan, F. V. Y. Tjong, "Optimizing patient selection for primary prevention implantable cardioverter-defibrillator implantation: utilizing multimodal machine learning to assess risk of implantable cardioverter-defibrillator non-benefit", EP Europace, 2023; 25 (9).
L. de Vries, R. L. M. van Herten, J. W. Hoving, I. Išgum, B. J. Emmer, C. B. L. M. Majoie, H. A. Marquering, E. Gavves, "Spatio-temporal physics-informed learning: A novel approach to CT perfusion analysis in acute ischemic stroke", Medical Image Analysis, 2023.
M. A. Molenaar, B. J. Bouma, C. F. Coerkamp, J. P. Man, I. Išgum, N. J. Verouden, J. L. Selder, S. A. J. Chamuleau, M. J. Schuuring, "The impact of valvular heart disease in patients with chronic coronary syndrome", Frontiers in Cardiovascular Medicine, 2023; 10.
J. Sander, B. D. de Vos, S. Bruns, N. Planken, M. A. Viergever, T. Leiner, I. Išgum, "Reconstruction and completion of high-resolution 3D cardiac shapes using anisotropic CMRI segmentations and continuous implicit neural representations", Computers in Biology and Medicine, 2023; 164.
B. Föllmer, M. C. Williams, D. Dey, A. Arbab-Zadeh, P. Maurovich-Horvat, R. H. J. A. Volleberg, D. Rueckert, J. A. Schnabel, D. E. Newby, M. R. Dweck, G. Guagliumi, V. Falk, A. J. Vázquez Mézquita, F. Biavati, I. Išgum & M. Dewey, "Roadmap on the use of artificial intelligence for imaging of vulnerable atherosclerotic plaque in coronary arteries", Nature Reviews Cardiology, 2023.
A. J. Vázquez Mézquita, F. Biavati, V. Falk, H. Alkadhi, R. Hajhosseiny, P. Maurovich-Horvat, R. Manka, S. Kozerke, M. Stuber, T. Derlin, K. M. Channon, I. Išgum, A. Coenen, B. Foellmer, D. Dey, R. H. J. A. Volleberg, F. G. Meinel, M. R. Dweck, J. J. Piek, T. van de Hoef, U. Landmesser, G. Guagliumi, A. A. Giannopoulos, R. M. Botnar, R. Khamis, M. C. Williams, D. E. Newby, M. Dewey, "Clinical quantitative coronary artery stenosis and coronary atherosclerosis imaging: a Consensus Statement from the Quantitative Cardiovascular Imaging Study Group", Nature Reviews Cardiology, 2023.
E. M. Postma, J. M.H. Noothout, W. M. Boek, A. Joshi, T. Herrmann, T. Hummel, P. A. M. Smeets, I. Išgum, S. Boesveldt, "The potential for clinical application of automatic quantification of olfactory bulb volume in MRI scans using convolutional neural networks", NeuroImage: Clinical, 2023.
A. Vos, I.B. Houben, C. Celeng, R.A.P. Takx, I. Isgum, W.P.T.M. Mali, A. Vink, P.A. de Jong, "Aortic calcification: A postmortem CT validation study in a middle-aged population", European Journal of Radiology , 2023.
R. Zoetmulder, L. Baak, N. Khalili, H.A. Marquering, N. Wagenaar, M. Benders, N.E. van der Aa, I. Isgum, "Brain segmentation in patients with perinatal arterial ischemic stroke", NeuroImage: Clinical, 2023: 103381.
L.S. ter Maat, I.A.J. van Duin, S.G. Elias, T. Leiner, J.J.C. Verhoeff, E.R.A.N. Arntz, M.F. Troenokarso, W.A.M. Blokx, I. Isgum, G.A. de Wit, F.W.P.J. van den Berkmortel, M.J. Boers-Sonderen, M.F. Boomsma, A.J.M. van den Eertwegh, J.W.B. de Groot, D. Piersma, G. Vreugdenhil, H.M Westgeest, E. Kapiteijn, P.J. van Diest, J.P.W. Pluim, P.A. de Jong, K.P.M. Suijkerbuijk and M. Veta, "CT radiomics compared to a clinical model for predicting checkpoint inhibitor treatment outcomes in patients with advanced melanoma", European Journal of Cancer, 2023.
M. Bourfiss, J. Sander, B.D. de Vos, A.S.J.M. te Riele, F.W. Asselbergs, I. Išgum and B.K. Velthuis , "Towards automatic classification of cardiovascular magnetic resonance Task Force Criteria for diagnosis of arrhythmogenic right ventricular cardiomyopathy", Clinical Research in Cardiology, 2023; 112 (3): 363-378.
R. Schwartz, H. Khalid, S. Liakopoulos, Y. Ouyang, C. de Vente, C. González-Gonzalo, A.Y. Lee, R. Guymer, E.Y. Chew and C. Egan, "A Deep Learning Framework for the Detection and Quantification of Reticular Pseudodrusen and Drusen on Optical Coherence Tomography", Translational Vision Science & Technology, 2022; 11 (12): 3-Mar.
A. Sitek, J. Seliga-Siwecka, S. Płotka, M. K. Grzeszczyk, S. Seliga, K. Włodarczyk, R. Bokiniec, "Artificial intelligence in the diagnosis of necrotising enterocolitis in newborns", Nature Pediatric Research, 2022.
N. Hampe, S.G.M. van Velzen, R.N. Planken, J.P. Henriques, C. Collet, J. Aben, M. Voskuil, T. Leiner and I. Isgum, "Deep Learning-based Detection of Functionally Significant Stenosis in Coronary CT Angiography", Frontiers in Cardiovascular Medicine, 2022; 15 (9): 964355.
Z. Zhai, S.G.M. van Velzen, N. Lessmann, N. Planken, T. Leiner and I. Isgum, "Learning coronary artery calcium scoring in coronary CTA from non-contrast CT using unsupervised domain adaptation", Frontiers in Cardiovascular Medicine, 2022; 9: 981901.
S.G.M. van Velzen, M.M. Dobrolinska, P. Knaapen, R.L.M. van Herten, R. Jukema, I. Danad, R.H.J.A. Slart, M.J.W. Greuter and I. Isgum, "Automated cardiovascular risk categorization through AI-driven coronary calcium quantification in cardiac PET acquired attenuation correction CT", Journal of Nuclear Cardiology, 2022.
P.M. Croon, J.L. Selder, C.P. Allaart, H. Bleijendaal, S.A.J. Chamuleau, L. Hofstra, I. Išgum, K.A. Ziesemer, M.M. Winter, "Current state of artificial intelligence based algorithms for hospital admission prediction in patients with heart failure-a scoping review", European Heart Journal-Digital Health, 2022; 3 (3): 415–425.
S.G.M. van Velzen, B.D. de Vos, J.M.H. Noothout, H.M. Verkooijen, M.A. Viergever, I. Išgum, "Generative models for reproducible coronary calcium scoring", Journal of Medical Imaging, 2022; 9 (5): 052406.
R. Zoetmulder, A.A.E. Bruggeman, I. Isgum, E. Gavves, C. Majoie, L. Beenen, D. Dippel, N. Boodt, S. Den Hartog, P.J. van Doormaal, S. Cornelissen, Y. Roos, J. Brouwer, W.J. Schonewille, A. Pirson, W. Van Zwam, C. van der Leij, R. Brans, A.C.G.M. van Es, H. Marquering, "Deep learning-based thrombus localization and segmentation in patients with posterior circulation stroke", Diagnostics, 2022; 12 (6): 1400.
J.M.H. Noothout, N. Lessmann, M.C. van Eede, L.D. van Harten, E. Sogancioglu, F.G. Heslinga, M. Veta, B. van Ginneken, I. Išgum, "Knowledge distillation with ensembles of convolutional neural networks for medical image segmentation", Journal of Medical Imaging, 2022; 9 (5): 1-20.
A. Vos, A. Vink, R. Kockelkoren, R.A.P Takx, C. Celeng, W.P.T.M. Mali, I. Isgum, R.L.A.W. Bleys, P.A. de Jong, "Radiography and computed tomography detection of intimal and medial calcifications in leg arteries in comparison to histology", Journal of Personalized Medicine, 2022; 12 (5): 711.
D. van Erck, P. Moeskops, J.D. Schoufour, P.J. Weijs, W.J. Scholte op Reimer, M.S. van Mourik, Y.C. Janmaat, R.N. Planken, M. Vis, J. Baan, R. Hemke, I. Isgum, J.P. Henriques, B.D. de Vos, R. Delewi, "Evaluation of a fully automatic deep learning-based method for the measurement of psoas muscle area", Frontiers in Nutrition, 2022; 9.
J. Sander, B.D. de Vos, I. Isgum, "Autoencoding low-resolution MRI for semantically smooth interpolation of anisotropic MRI", Medical Image Analysis, 2022; 78: 102393.
L.D. van Harten, C.S. de Jonge, K.J. Beek, J. Stoker, I. Isgum, "Untangling and segmenting the small intestine in 3D cine-MRI using deep learning", Medical Image Analysis, 2022; 78: 102386.
D. Ties, P. van Dorp, G. Pundziute, C.M. van der Aalst, J.W.C. Gratama, R.L. Braam, D. Kuijpers, D.D. Lubbers, I.A.C. van der Bilt, B.D. Westenbrink, M.J. Oude Wolcherink, C.J.M. Doggen, I. Isgum, R. Nijveldt, H.J. de Koning, R. Vliegenthart, M. Oudekerk, P. van der Harst, "Early detection of obstructive coronary artery disease in the asymptomatic high-risk population: objectives and study design of the EARLY-SYNERGY trial", American Heart Journal, 2022; 246: 166-177.
S. Bruns, J.M. Wolterink, T.P.W. van den Boogert, J.H. Runge, B.J. Bouma, J.P. Henriques, J. Baan, M.A. Viergever, R.N. Planken, I. Isgum, "Deep learning-based whole-heart segmentation in 4D contrast-enhanced cardiac CT", Computers in Biology and Medicine, 2022; 142: 105191.
C. González-Gonzalo, E. F. Thee, C. W. Klaver, A. Y. Lee, R. O. Schlingemann, A. Tufail, F. Verbraak and C. I. Sánchez, "Trustworthy AI: Closing the gap between development and integration of AI systems in ophthalmic practice", Progress in Retinal and Eye Research, 2022; 90: 101034.
A. Schreuder, C. Jacobs, N. Lessmann, M.J.M. Broeders, M. Silva, I. Isgum, P.A. de Jong, M.M. van den Heuvel, N. Sverzellati, M. Prokop, U. Pastorino, C.M. Schaefer-Prokop, B. van Ginneken, "Scan-based competing death risk model for reevaluating lung cancer computed tomography screening eligibility", European Respiratory Journal, 2022; 59 (5).
S.G.M. van Velzen, R. Gal, A.J. Teske, F. van der Leij, D.H.J.G. van den Bongard, M.A. Viergever, H.M. Verkooijen, I. Isgum, "AI-based radiation dose quantification for estimation of heart disease risk in breast cancer survivors after radiation therapy", International Journal of Radiation Oncology, 2022; 112 (3): 621-632.
S.G.M. van Velzen, S. Bruns, J.M. Wolterink, T. Leiner, M.A. Viergever, H.M. Verkooijen, I. Išgum, "AI-based quantification of planned radiation therapy dose to cardiac structures and coronary arteries in patients with breast cancer", International Journal of Radiation Oncology, Biology, Physics, 2022; 112 (3): 611-620.
C. de Vente, L. Boulogne, K. Venkadesh, C. Sital, N. Lessmann, C. Jacobs, C. Sánchez and B. van Ginneken, "Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: A Systematic Comparison", IEEE Transactions on Artificial Intelligence, 2021; 3 (2): 129-138.
R. Gal, M.L. Gregorowitsch, M.J. Emaus, E.L.A. Blezer, F. van der Leij, S.G.M. van Velzen, J.J. van Tol-Geerdink, I. Isgum, H.M. Verkooijen, "Coronary artery calcifications on breast cancer radiotherapy planning CT scans and cardiovascular risk: What do patients want to know?", International Journal of Cardiology Cardiovascular Risk and Prevention, 2021; 11 : 200113.
M. Dekker, F. Waissi, M.J.M. Silvis, J.V. Bennekom, A.H. Schoneveld, R.J. de Winter, I. Isgum, N. Lessmann, B.K. Velthuis, G. Pasterkamp, A. Mosterd, L. Timmers, D.P.V. de Kleijn, "High levels of osteoprotegerin are associated with coronary artery calcification in patients suspected of a chronic coronary syndrome", Nature Scientific Reports, 2021; 11 (18946): 1-10.
A. Schreuder, C. Jacobs, N. Lessmann, M.J.M. Broeders, M. Silva, I. Isgum, P.A. de Jong, N. Sverzellati, M. Prokop, U. Pastorino, C.M. Schaefer-Prokop, B. van Ginneken, "Combining pulmonary and cardiac computed tomography biomarkers for disease-specific risk modelling in lung cancer screening", European Respiratory Journal, 2021; 58 (3).
R. Zoetmulder, P.R. Konduri, I.V. Obdeijn, E. Gavves, I. Išgum, C.B.L.M. Majoie, D.W.J. Dippel, Y.B.W.E.M. Roos, M. Goyal, P.J. Mitchell, B.C.V. Campbell, D.K. Lopes, G. Reimann, T.G. Jovin, J.L. Saver, K.W. Muir, P. White, S. Bracard, B. Chen, S. Brown, W.J. Schonewille, E. van der Hoeven, V. Puetz, H.A. Marquering, "Automated Final Lesion Segmentation in Posterior Circulation Acute Ischemic Stroke Using Deep Learning", Diagnostics, 2021; 11 (9): 1621.
G. Bortsova, C. González-Gonzalo, S. Wetstein, F. Dubost, I. Katramados, L. Hogeweg, B. Liefers, B. van Ginneken, J. Pluim, M. Veta, C. Sánchez and M. de Bruijne, "Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors", Medical Image Analysis, 2021; 73: 102141.
R. Gal, S.G.M. van Velzen, M.J. Hooning, M.J. Emaus, F. van der Leij, M.L. Gregorowitsch, E.L.A. Blezer, S.A.M. Gernaat, N. Lessmann, M.G.A. Sattler, T. Leiner, P.A. de Jong, A.J. Teske, J. Verloop, J.J. Penninkhof, I. Vaartjes, H. Meijer, J.J. van Tol-Geerdink, J. Pignol, D.H.J.G. van den Bongard, I. Išgum, H.M. Verkooijen, "Identification of risk of cardiovascular disease by automatic quantification of coronary artery calcifications on radiotherapy planning CT scans in patients with breast cancer", JAMA Oncology, 2021; 7 (7): 1024-1032.
J.M. Wolterink, A. Mukhopadhyay, T. Leiner, T.J. Vogl, A.M. Bucher, I. Išgum , "Generative adversarial networks: A primer for radiologists", Radiographics, 2021; 41 (3): 840-857.
R.H.J.A. Slart, M.C. Williams, L.E. Juarez-Orozco, C. Rischpler, M.R. Dweck, A.W.J.M. Glaudemans, A. Gimelli, P. Georgoulias, O. Gheysens, O. Gaemperli, G. Habib, R. Hustinx, B. Cosyns, H.J. Verberne, F. Hyafil, P.A. ErbaA, M. Lubberink, P. Slomka, I. Išgum, D. Visvikis, M. Kolossváry, A. Saraste , "Position paper of the EACVI and EANM on artificial intelligence applications in multimodality cardiovascular imaging using SPECT/CT, PET/CT, and cardiac CT", European Journal of Nuclear Medicine and Molecular Imaging, 2021; 48(5): 1399-1413.
B.D. de Vos, N. Lessmann, P.A. de Jong, I. Isgum, "Deep learning–quantified calcium scores for automatic cardiovascular mortality prediction at lung screening low-dose CT", Radiology Cardiothoracic Imaging, 2021; 3 (2): e190219.
M. Dekker, F. Waissi, I.E.M. Bank, I. Isgum, A.M. Scholtens, B.K. Velthuis, G. Pasterkamp, R.J. de Winter, A. Mosterd, L. Timmers, D.P.V. de Kleijn, "The prognostic value of automated coronary calcium derived by a deep learning approach on non-ECG gated CT images from 82 Rb-PET/CT myocardial perfusion imaging", International Journal of Cardiology, 2021; 329: 9-15.
M.J. Schuuring, I. Išgum, B. Cosyns, S.A.J. Chamuleau, B.J. Bouma , "Routine echocardiography and artificial intelligence solutions", Frontiers in Cardiovascular Medicine, 2021; 8: 648877.
A. Lin, M. Kolossváry, M. Motwani, I. Išgum, P. Maurovich-Horvat, P.J. Slomka, D. Dey, "Artificial intelligence in cardiovascular imaging for risk stratification in coronary artery disease", Radiology: Cardiothoracic Imaging, 2021; 3 (1): e200512.
A. Lin, M. Kolossváry, M. Motwani, I. Išgum, P. Maurovich-Horvat, P.J. Slomka, D. Dey, "Artificial intelligence in cardiovascular CT: Current status and future implications", Journal of Cardiovascular Computed Tomography, 2021; 15 (6): 462-469.
N. Lessmann, C. I. Sánchez, L. Beenen, L. H. Boulogne, M. Brink, E. Calli, J. Charbonnier, T. Dofferhoff, W. M. van Everdingen, P. K. Gerke, B. Geurts, H. A. Gietema, M. Groeneveld, L. van Harten, N. Hendrix, W. Hendrix, H. J. Huisman, I. Isgum, C. Jacobs, R. Kluge, M. Kok, J. Krdzalic, B. Lassen-Schmidt, K. van Leeuwen, J. Meakin, M. Overkamp, T. van Rees Vellinga, E. M. van Rikxoort, R. Samperna, C. Schaefer-Prokop, S. Schalekamp, E. T. Scholten, C. Sital, L. Stöger, J. Teuwen, K. Vaidhya Venkadesh, C. de Vente, M. Vermaat, W. Xie, B. de Wilde, M. Prokop and B. van Ginneken, "Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence", Radiology, 2021; 298 (1): E18-E28.
B. Liefers, P. Taylor, A. Alsaedi, C. Bailey, K. Balaskas, N. Dhingra, C. A. Egan, F. G. Rodrigues, C. González-Gonzalo, T. F. C. Heeren, A. Lotery, P. L. Muller, A. Olvera-Barrios, B. Paul, R. Schwartz, D. S. Thomas, A. N. Warwick, A. Tufail and C. I. Sánchez, "Quantification of key retinal features in early and late age-related macular degeneration using deep learning", American Journal of Ophthalmology, 2021.
Z. Xiong, Q. Xia, Z. Hu, N. Huang, C. Bian, Y. Zheng, S. Vesal, N. Ravikumar, A. Maier, X. Yang, P. Heng, D. Ni, C. Li, Q. Tong, W. Si, E. Puybareau, Y. Khoudli, T. Géraud, C. Chen, W. Bai, D. Rueckert, L. Xu, X. Zhuang, X. Luo, S. Jia, M. Sermesant, Y. Liu, K. Wang, D. Borra, A. Masci, C. Corsi, C. de Vente, M. Veta, R. Karim, C. J. Preetha, S. Engelhardt, M. Qiao, Y. Wang, Q. Tao, M. Nuñez-Garcia, O. Camara, N. Savioli, P. Lamata, J. Zhao, "A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging", Medical Image Analysis, 2021; 67.
de Vente, Coen and Vos, Pieter and Hosseinzadeh, Matin and Pluim, Josien and Veta, Mitko, "Deep learning regression for prostate cancer detection and grading in bi-parametric MRI", IEEE Transactions on Biomedical Engineering, 2020; 68 (2): 374-383.
E. F. Thee, D. T. Luttikhuizen, H. G. Lemij, F. D. Verbraak, C. I. Sánchez and C. C. W. Klaver, "Artificial intelligence for eye care", Nederlands Tijdschrift voor Geneeskunde, 2020.
B. Liefers, J. M. Colijn, C. González-Gonzalo, T. Verzijden, J. J. Wang, N. Joachim, P. Mitchell, C. B. Hoyng, B. van Ginneken, C. C. Klaver and C. I. Sánchez, "A deep learning model for segmentation of geographic atrophy to study its long-term natural history", Ophthalmology, 2020; 127 (8): 1086-1096.
C. González-Gonzalo, B. Liefers, B. van Ginneken and C. I. Sánchez, "Iterative augmentation of visual evidence for weakly-supervised lesion localization in deep interpretability frameworks: application to color fundus images", IEEE Transactions on Medical Imaging, 2020; 39 (11): 3499-3511.
C. González-Gonzalo, V. Sánchez-Gutiérrez, P. Hernández-Martínez, I. Contreras, Y. T. Lechanteur, A. Domanian, B. van Ginneken and C. I. Sánchez, "Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age-related macular degeneration", Acta Ophthalmologica, 2020; 98 (4): 368-377.
S. G. M. van Velzen, N. Lessmann, B. K. Velthuis, I. E. M. Bank, D. H. J. G. van den Bongard, T. Leiner, P. A. de Jong, W. B. Veldhuis, A. Correa, J. G. Terry, J. J. Carr, M. A. Viergever, H. M. Verkooijen and I. Išgum, "Deep learning for automatic calcium scoring in CT: validation using multiple cardiac CT and chest CT protocols", Radiology, 2020; 295 (1).
C. Beijst, J. Dudink, R. Wientjes, I. Benavente-Fernandez, F. Groenendaal, M. J. Brouwer, I. Išgum, H. W. A. M. de Jong and L. S. de Vries, "Two-dimensional ultrasound measurements vs. magnetic resonance imaging-derived ventricular volume of preterm infants with germinal matrix intraventricular haemorrhage", Pediatric Radiology, 2020; 50 (2): 234-241.
J. W. Bartstra, P. A. de Jong, G. Kranenburg, J. M. Wolterink, I. Išgum, A. Wijsman, B. Wolf, A. M. den Harder, W. P. T. M. Mali and W. Spiering, "Etidronate halts systemic arterial calcification in pseudoxanthoma elasticum", Atherosclerosis, 2020; 292: 37-41.
J. Sander, B. D. de Vos and I. Išgum, "Automatic segmentation with detection of local segmentation failures in cardiac MRI", Scientific Reports, 2020; 10 (21769).
S. Bruns, J. M. Wolterink, R. A. P. Takx, R. W. van Hamersvelt, D. Suchá, M. A. Viergever, T. Leiner and I. Išgum, "Deep learning from dual-energy information for whole-heart segmentation in dual-energy and single-energy non-contrast-enhanced cardiac CT", Medical Physics, 2020; 47 (10): 5048-5060.
J. M. H. Noothout, B. D. de Vos, J. M. Wolterink, E. M. Postma, P. A. M. Smeets, R. A. P. Takx, T. Leiner, M. A. Viergever and I. Išgum, "Deep learning-based regression and classification for automatic landmark localization in medical images", IEEE Transactions on Medical Imaging, 2020; 39 (12): 4011-4022.
A. Lin, M. Kolossváry, I. Išgum, P. Maurovich-Horvat, P. J. Slomka and D. Dey, "Artificial intelligence: improving the efficiency of cardiovascular imaging", Expert Review of Medical Devices, 2020; 17 (6): 565-577.
P. J. Slomka, R. J. H. Miller, I. Išgum and D. Dey, "Application and translation of artificial intelligence to cardiovascular imaging in nuclear medicine and noncontrast CT", Seminars in Nuclear Medicine, 2020; 50 (4): 357-366.
M. Zreik, R. W. van Hamersvelt, N. Khalili, J. M. Wolterink, M. Voskuil, M. A. Viergever, T. Leiner and I. Išgum, "Deep learning analysis of coronary arteries in cardiac CT angiography for detection of patients requiring invasive coronary angiography", IEEE Transactions on Medical Imaging, 2020; 39 (5): 1545-1557.
C. Celeng, R. A. P. Takx, N. Lessmann, P. Maurovich-Horvat, T. Leiner, I. Išgum and P. A. de Jong, "The association between marital status, coronary computed tomography imaging biomarkers, and mortality in a lung cancer screening population", Journal of Thoracic Imaging, 2020; 35 (3): 204-209.
C. C. van 't Klooster, H. M. Nathoe, J. .Hjortnaes, M. L. Bots, I. Išgum, N. Lessmann, Y. van der Graaf, T. Leiner, F. L. J. Visseren and O. U. behalf of the group, "Multifocal cardiovascular calcification in patients with established cardiovascular disease; prevalence, risk factors, and relation with recurrent cardiovascular disease", International Journal of Cardiology, Heart amp; Vasculature, 2020; 27 (100499).
R.W. van Hamersvelt, M. Voskuil, P.A de Jong, M.J. Willemink, I. Išgum, T. Leiner, "Diagnostic performance of on-site coronary CT angiography-derived fractional flow reserve based on patient-specific lumped parameter models", Radiology Cardiothoracic Imaging , 2019; 1 (4): e190036..
M.N. Cizmeci, N. Khalili, N.H.P. Claessens, F. Groenendaal, K.D. Liem, A. Heep, I. Benavente-Fernández, H.L.M. van Straaten, G. van Wezel-Meijler, S.J. Steggerda, J. Dudink, I. Išgum, A.Whitelaw, M.J.N.L. Benders, L.S. de Vries; ELVIS study group, "Assessment of brain injury and brain volumes after posthemorrhagic ventricular dilatation: A nested substudy of the randomized controlled ELVIS Trial", The Journal of Pediatrics, 2019; 208: 191-197.e2.
V. Schreur, A. Domanian, B. Liefers, F. G. Venhuizen, B. J. Klevering, C. B. Hoyng, E. K. de Jong and T. Theelen, "Morphological and topographical appearance of microaneurysms on optical coherence tomography angiography", British Journal of Ophthalmology, 2019; 103 (5): 630-635.
V. Schreur, A. de Breuk, F. G. Venhuizen, C. I. Sánchez, C. J. Tack, B. J. Klevering, E. K. de Jong and C. B. Hoyng, "Retinal hyperreflective foci in type 1 diabetes mellitus", Retina, 2019.
D. Valkenburg, E. H. Runhart, N. M. Bax, B. Liefers, S. L. Lambertus, C. I. Sánchez, F. P. Cremers and C. B. Hoyng, "Highly variable disease courses in siblings with Stargardt disease", Ophthalmology, 2019; 126: 1712-1721.
R. H. H. M. Philipsen, C. I. Sánchez, J. Melendez, W. J. Lew and B. van Ginneken, "Automated chest X-ray reading for tuberculosis in the Philippines to improve case detection: a cohort study", International Journal of Tuberculosis and Lung Disease, 2019; 23: 805-810.
T. J. Heesterbeek, E. K. de Jong, I. E. Acar, J. M. M. Groenewoud, B. Liefers, C. I. Sánchez, T. Peto, C. B. Hoyng, D. Pauleikhoff, H. W. Hense and A. I. den Hollander, "Genetic risk score has added value over initial clinical grading stage in predicting disease progression in age-related macular degeneration", Nature Scientific Reports, 2019; 9: 6611.
R. P. Finger, S. Schmitz-Valckenberg, M. Schmid, G. S. Rubin, H. Dunbar, A. Tufail, D. P. Crabb, A. Binns, C. I. Sánchez, P. Margaron, G. Normand, M. K. Durbin, U. F. O. Luhmann, P. Zamiri, J. Cunha-Vaz, F. Asmus, F. G. Holz and O. M. behalf of the consortium, "MACUSTAR: Development and Clinical Validation of Functional, Structural, and Patient-Reported Endpoints in Intermediate Age-Related Macular Degeneration", Ophthalmologica, 2019; 241: 61-72.
J. J. Gómez-Valverde, A. Antón, G. Fatti, B. Liefers, A. Herranz, A. Santos, C. I. Sánchez and M. J. Ledesma-Carbayo, "Automatic glaucoma classification using color fundus images based on convolutional neural networks and transfer learning", Biomedical Optics Express, 2019; 10 (2): 892-913.
H. Bogunovic, F. Venhuizen, S. Klimscha, S. Apostolopoulos, A. Bab-Hadiashar, U. Bagci, M. F. Beg, L. Bekalo, Q. Chen, C. Ciller, K. Gopinath, A. K. Gostar, K. Jeon, Z. Ji, S. H. Kang, D. D. Koozekanani, D. Lu, D. Morley, K. K. Parhi, H. S. Park, A. Rashno, M. Sarunic, S. Shaikh, J. Sivaswamy, R. Tennakoon, S. Yadav, S. De Zanet, S. M. Waldstein, B. S. Gerendas, C. Klaver, C. I. Sánchez and U. Schmidt-Erfurth, "RETOUCH: The Retinal OCT Fluid Detection and Segmentation Benchmark and Challenge", IEEE Transactions on Medical Imaging, 2019; 38: 1858-1874.
N. Lessmann, B. van Ginneken, P. A. de Jong and I. Išgum, "Iterative fully convolutional neural networks for automatic vertebra segmentation and identification", Medical Image Analysis, 2019; 53: 142-155.
R. W. van Hamersvelt, I. Išgum, P. A. de Jong, M. J. Cramer, G. E. Leenders, M. J. Willemink, M. Voskuil and T. Leiner, "Application of speCtraL computed tomogrAphy to impRove specIficity of cardiac compuTed tomographY (CLARITY study): Rationale and Design", BMJ Open, 2019; 9 (3): e025793.
N. Lessmann, P. A. de Jong, C. Celeng, R. A. P. Takx, M. A. Viergever, B. van Ginneken and I. Išgum, "Sex differences in coronary artery and thoracic aorta calcification and their association with cardiovascular mortality in heavy smokers", JACC: Cardiovascular Imaging, 2019; 12 (9): 1808-1817.
J. M. Wolterink, R. W. van Hamersvelt, M. A. Viergever, T. Leiner and I. Išgum, "Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier", Medical Image Analysis, 2019; 51: 46-60.
M. Zreik, R. W. van Hamersvelt, J. M. Wolterink, T. Leiner, M. A. Viergever and I. Išgum, "A recurrent CNN for automatic detection and classification of coronary artery plaque and stenosis in coronary CT angiography", IEEE Transactions on Medical Imaging, 2019; 38 (7): 1588-1598.
R. W. van Hamersvelt*, M. Zreik*, M. Voskuil, M. A. Viergever, I. Išgum and T. Leiner, "Deep learning analysis of left ventricular myocardium in CT angiographic intermediate degree coronary stenosis improves the diagnostic accuracy for identification of functionally significant stenosis", European Radiology, 2019; 29 (5): 2350-2359.
E. Verburg, J. M. Wolterink, S. N. de Waard, I. Išgum, C. H. van Gils, W. B. Veldhuis and K. G. A. Gilhuijs, "Knowledge-based and deep learning-based automated chest wall segmentation in Magnetic Resonance Images of extremely dense breasts", Medical physics, 2019; 46 (10): 4405-4416.
N. Khalili, N. Lessmann, E. Turk, N. Claessens, R. de Heus, T. Kolk, M. A. Viergever, M. J. N. L. Benders and I. Išgum, "Automatic brain tissue segmentation in fetal MRI using convolutional neural networks", Magnetic Resonance Imaging, 2019; 64: 77-89.
J. W. Benjamins, K. van Leeuwen, L. Hofstra, M. Rienstra, Y. Appelman, W. Nijhof, B. Verlaat, I. Everts, H. M. den Ruijter, I. Išgum, T. Leiner, R. Vliegenthart, F. W. Asselbergs, L. E. Juarez-Orozco and P. van der Harst, "Enhancing cardiovascular artificial intelligence (AI) research in the Netherlands: CVON-AI consortium", Netherlands Heart Journal, 2019; 27: 414-425.
N. H. P. Claessens, N. Khalili, I. Išgum, H. ter Heide, T. J. Steenhuis, E. Turk, N. J. G. Jansen, L. S. de Vries, J. M. P. J. Breur, R. de Heus and M. J. N. L. Benders, "Brain and cerebrospinal fluid volumes in fetuses and neonates with antenatal diagnosis of critical congenital heart disease: a longitudinal MRI study", American Journal of Neuroradiology, 2019.
B. D. de Vos, J. M. Wolterink, T. Leiner, P. A. de Jong, N. Lessmann and I. Išgum, "Direct automatic coronary calcium scoring in cardiac and chest CT", IEEE Transactions on Medical Imaging, 2019; 34: 123-136.
B. D. de Vos, F. F. Berendsen, M. A. Viergever, H. Sokooti, M. Staring and I. Išgum, "A deep learning framework for unsupervised affine and deformable image registration", Medical Image Analysis, 2019; 52: 128 - 143.
N. Hampe, J. M. Wolterink, S. G. M. van Velzen, T. Leiner and I. Išgum, "Machine learning for assessment of coronary artery disease in cardiac CT: a survey", Frontiers in Cardiovascular Medicine, 2019; 6 (172).
M. Dekker, F. Waissi, I. E. M. Bank, N. Lessmann, I. Išgum, B. K. Velthuis, A. M. Scholtens, G. E. Leenders, G. Pasterkamp, D. P. V. de Kleijn, L. Timmers and A. Mosterd, "Automated calcium scores collected during myocardial perfusion imaging improve identification of obstructive coronary artery disease", IJC Heart & Vasculature, 2019; 26 (100434).
N. Khalili, E.Turk, M. J. N. L. Benders, P. Moeskops, N. H. P. Claessens, R. de Heuse, A. Franx, N. Wagenaar, J. M. P. J. Breur, M. A. Viergever and I. Išgum, "Automatic extraction of the intracranial volume in fetal and neonatal MR scans using convolutional neural networks", NeuroImage Clinical, 2019; 24 (102061).
T. Leiner, D. Rueckert, A. Suinesiaputra, B. Baeßler, R. Nezafat, I. Išgum and A. A. Young, "Machine learning in cardiovascular magnetic resonance: basic concepts and applications", Journal of Cardiovascular Magnetic Resonance, 2019; 21 (1): 61.
G. Litjens, F. Ciompi, J. M. Wolterink, B. D. de Vos, T. Leiner, J. Teuwen and I. Išgum, "State-of-the-art deep learning in cardiovascular image analysis", JACC: Cardiovascular Imaging, 2019; 12 (8 Part 1): 1549-1565.
M. J. Emaus, I. Išgum, S. G. M. van Velzen, H. J. G. D. van den Bongard, S. A. M. Gernaat, N. Lessmann, M. G. A. Sattler, A. J. Teske, J. Penninkhof, H. Meijer, J. P. Pignol and H. M. V. B. study group, "Bragatston study protocol: a multicentre cohort study on automated quantification of cardiovascular calcifications on radiotherapy planning CT scans for cardiovascular risk prediction in patients with breast cancer", BMJ Open, 2019; 9 (7): e028752.
K. Keunen, H.K. van der Burgh, M.A. de Reus, P. Moeskops, R. Schmidt, L.J. Stolwijk, S.C. de Lange, I. Išgum, L.S. de Vries, M.J.N.L. Benders, M.P. van den Heuvel, "Early human brain development: insights into macroscale connectome wiring", Pediatric Research, 2018; 84 (6): 829-836.
F. G. Venhuizen, B. van Ginneken, B. Liefers, F. van Asten, V. Schreur, S. Fauser, C. B. Hoyng, T. Theelen and C. I. Sánchez, "A Deep Learning Approach for Detection and Quantification of Intraretinal Cystoid Fluid in Multivendor Optical Coherence Tomography", Biomedical Optics Express, 2018; 9 (4): 1545-1569.
J. Melendez, L. Hogeweg, C. I. Sánchez, R. H. H. M. Philipsen, R. W. Aldridge, A. C. Hayward, I. Abubakar, B. van Ginneken and A. Story, "Accuracy of an automated system for tuberculosis detection on chest radiographs in high-risk screening", International Journal of Tuberculosis and Lung Disease, 2018; 22 (5): 567-571.
C. Coviello, K. Keunen, K. J. Kersbergen, F. Groenendaal, A. Leemans, B. Peels, I. Isgum, M. A. Viergever, L. S. de Vries, G. Buonocore, V. P. Carnielli and M. J. N. L. Benders, "Effects of early nutrition and growth on brain volumes, white matter microstructure and neurodevelopmental outcome in preterm newborns, in print", Pediatric Research, 2018; 83: 102-110.
I. Isgum, B. D. de Vos, J. M. Wolterink, D. Dey, D. S. Berman, M. Rubeaux, T. Leiner and P. J. Slomka, "Erratum to: Automatic determination of cardiovascular risk by CT attenuation correction maps in Rb-82 PET/CT", Journal of Nuclear Cardiology, 2018; 25 (6): 2143.
I. Isgum, B. D. de Vos, J. M. Wolterink, D. Dey, D. S. Berman, M. Rubeaux, T. Leiner and P. J. Slomka, "Automatic determination of cardiovascular risk by CT attenuation correction maps in Rb-82 PET/CT", Journal of Nuclear Cardiology, 2018; 25 (6): 2133-2142.
O. Bernard, A. Lalande, C. Zotti, F. Cervenansky, X. Yang, P. Heng, I. Cetin, K. Lekadir, O. C. M. G. Ballester, G. Sanroma, S. Napel, S. Petersen, G. Tziritas, E. Grinias, M. Khened, V. A. Kollerathu, G. Krishnamurthi, M. Rohé, X. Pennec, M. Sermesant, F. Isensee, P. Jäger, K. H. Maier-Hein, C. F. Baumgartner, L. M. Koch, J. M. Wolterink, I. Išgum, Y. Jang, Y. Hong, J. Patravali, S. Jain, O. Humbert and P. Jodoin, "Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: Is the problem solved?", IEEE Transactions on Medical Imaging, 2018; 37 (11): 2514-2525.
S. A. M. Gernaat, S. G. M. van Velzen, V. Koh, M. J. Emaus, I. Išgum, N. Lessmann, S. Moes, A. Jacobson, P. W. Tan, D. E. Grobbee, D. H. J. van den Bongard, J. I. Tang and H. M. Verkooijen, "Automatic quantification of calcifications in the coronary arteries and thoracic aorta on radiotherapy planning CT scans of Western and Asian breast cancer patients", Radiotherapy and Oncology, 2018; 127 (3): 487-492.
N. Lessmann, B. van Ginneken, M. Zreik, P. A. de Jong, B. D. de Vos, M. A. Viergever and I. Išgum, "Automatic calcium scoring in low-dose chest CT using deep neural networks with dilated convolutions", IEEE Transactions on Medical Imaging, 2018; 37 (2): 615-625.
M. Zreik, N. Lessmann, R. W. van Hamersvelt, J. M. Wolterink, M. Voskuil, M. A. Viergever, T. Leiner and I. Išgum, "Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis", Medical Image Analysis, 2018; 44: 72-85.
R. E. M. Senden, K. Keunen, N. E. van der Aa, A. Leemans, I. Išgum, M. A. Viergever, J. Dudink, L. S. de Vries, F. Groenendaal and M. J. N. L. Benders, "Mild cerebellar injury does not significantly affect cerebral white matter microstructural organization and neurodevelopmental outcome in a contemporary cohort of preterm infants", Pediatric Research, 2018; 83: 1004-1010.
M. L. Tataranno, N. H. P. Claessens, P. Moeskops, M. C. Toet, K. J. Kersbergen, G. Buonocore, I. Išgum, A. Leemans, S. Counsell, F. Groenendaal, L. S. de Vries and M. J. N. L. Benders, "Changes in brain morphology and microstructure in relation to early brain activity in extremely preterm infants", Pediatric Research, 2018; 83 (4): 834-842.
F. J. Drost, K. Keunen, P. Moeskops, N. H. P. Claessens, F. van Kalken, I. Išgum, E. S. M. Voskuil-Kerkhof, F. Groenendaal, L. S. de Vries, M. J. N. L. Benders and J. U. M. Termote, "Severe retinopathy of prematurity is associated with reduced cerebellar and brainstem volumes at term and neurodevelopmental deficits at two years", Pediatric Research, 2018; 83: 818-824.
J. Šprem, B. D. de Vos, N. Lessmann, R. W. van Hamersvelt, M. J. W. Greuter, P. A. de Jong, T. Leiner, M. A. Viergever and I. Išgum, "Coronary calcium scoring with partial volume correction in anthropomorphic thorax phantom and screening chest CT images", PLoS One, 2018; 13 (12): e0209318.
J. Šprem, B. D. de Vos, N. Lessmann, P. A. de Jong, M. A. Viergever and I. Išgum, "Impact of automatically detected motion artifacts on coronary calcium scoring in chest CT", Journal of Medical Imaging, 2018; 5 (4): 44007.
N. H. P. Claessens, S. O. Algra, T. L. Ouwehand, N. J. G. Jansen, R. Schappin, F. Haas, M. J. C. Eijsermans, L. S. de Vries, M. J. N. L. Benders, C. L. S. G. Utrecht, P. Moeskops, I. Išgum, I. C. van Haastert, F. Groenendaal and J. M. P. J. Breur, "Perioperative neonatal brain injury is associated with worse school‐age neurodevelopment in children with critical congenital heart disease", Developmental medicine and child neurology, 2018; 60 (10): 1052-1058..
A. M. den Harder, P. A. de Jong, M. C. H. de Groot, J. M. Wolterink, R. P. J. Budde, I. Išgum, W. W. van Solinge, M. J. T. Berg, E. Lutgens, W. B. Veldhuis, S. Haitjema, I. E. Hoefer and T. Leiner, "Commonly available hematological biomarkers are associated with the extent of coronary calcifications", Atherosclerosis, 2018; 275: 166-173.
A. Vos, G. Kranenburg, P. A. de Jong, W. P. T. M. Mali, W. van Hecke, R. L. A. W. Bleys, I. Išgum, A. Vink and W. Spiering, "The amount of calcifications in pseudoxanthoma elasticum patients is underestimated in computed tomographic imaging; a post-mortem correlation of histological and computed tomographic findings in two cases", Insights Imaging, 2018; 9 (4): 493-498.
A. M. Dinkla, J. M. Wolterink, M. Maspero, M. H. F. Savenije, J. J. C. Verhoeff, E. Seravalli, I. Išgum, P. R. Seevinck and C. A. T. van den Berg, "MR-only brain radiotherapy: Dosimetric evaluation of synthetic CTs generated by a dilated convolutional neural network", International Journal of Radiation Oncology, Biology, Physics, 2018; 102 (4): 810-812.
F. G. Venhuizen, B. van Ginneken, F. van Asten, M. J. van Grinsven, S. Fauser, C. B. Hoyng, T. Theelen and C. I. Sánchez, "Automated Staging of Age-Related Macular Degeneration Using Optical Coherence Tomography", Investigative Ophthalmology and Visual Science, 2017; 58 (4): 2318-2328.
F. G. Venhuizen, B. van Ginneken, B. Liefers, Schreur, M. J. van Grinsven, S. Fauser, C. B. Hoyng, T. Theelen and C. I. Sánchez, "Robust Total Retina Thickness Segmentation in Optical Coherence Tomography Images using Convolutional Neural Networks", Biomedical Optics Express, 2017; 8 (7): 3292-3316.
R. Manniesing, M. T. Oei, L. J. Oostveen, J. Melendez, E. J. Smit, B. Platel, C. I. Sánchez, F. J. Meijer, M. Prokop and B. van Ginneken, "White Matter and Gray Matter Segmentation in 4D Computed Tomography", Nature Scientific Reports, 2017; 7 (119).
T. Kooi, G. Litjens, B. van Ginneken, A. Gubern-Mérida, C. I. Sánchez, R. Mann, A. den Heeten and N. Karssemeijer, "Large scale deep learning for computer aided detection of mammographic lesions", Medical Image Analysis, 2017; 35: 303-312.
B. Liefers, F. G. Venhuizen, V. Schreur, B. van Ginneken, C. Hoyng, S. Fauser, T. Theelen and C. I. Sánchez, "Automatic detection of the foveal center in optical coherence tomography", Biomedical Optics Express, 2017; 8 (11): 5160-5178.
G. Litjens, T. Kooi, B. Ehteshami Bejnordi, A. A. A. Setio, F. Ciompi, M. Ghafoorian, J. A. W. M. van der Laak, B. van Ginneken and C. I. Sánchez, "A Survey on Deep Learning in Medical Image Analysis", Medical Image Analysis, 2017; 42: 60-88.
L. Hogeweg, C. I. Sánchez, P. Maduskar, R. H. H. M. Philipsen and B. van Ginneken, "Fast and effective quantification of symmetry in medical images for pathology detection: application to chest radiography", Medical Physics, 2017; 44 (6): 2242-2256.
L. Gallardo-Estrella, E. Pompe, P. A. de Jong, C. Jacobs, E. M. van Rikxoort, M. Prokop, C. I. Sánchez and B. van Ginneken, "Normalized emphysema scores on low dose CT: Validation as an imaging biomarker for mortality", PLoS One, 2017; 12: e0188902.
M. Ghafoorian, N. Karssemeijer, T. Heskes, I. van Uden, C. I. Sánchez, G. Litjens, F. de Leeuw, B. van Ginneken, E. Marchiori and B. Platel, "Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities", Nature Scientific Reports, 2017; 7 (1): 5110.
P. Moeskops, J. de Bresser, H. J. Kuijf, A. M. Mendrik, G. J. Biessels, J. P. Pluim and I. Išgum, "Evaluation of a deep learning approach for the segmentation of brain tissues and white matter hyperintensities of presumed vascular origin in MRI", NeuroImage Clinical, 2017; 17: 251-262.
J. M. Wolterink, T. Leiner, M. A. Viergever and I. Isgum, "Generative adversarial networks for noise reduction in low-dose CT", IEEE Transactions on Medical Imaging, 2017; 36 (12): 2536 - 2545.
P. Moeskops, I. Isgum, K. Keunen, N. H. P. Claessens, I. C. van Haastert, F. Groenendaal, L. S. de Vries, M. A. Viergever and M. J. N. L. Benders, "Prediction of cognitive and motor outcome of preterm infants based on automatic quantitative descriptors from neonatal MR brain images", Scientific Reports, 2017; 7 (2163).
E. Pompe, P. A. de Jong, D. A. Lynch, N. Lessmann, I. Isgum, B. van Ginneken, J. -. J. Lammers and F. A. A. M. Hoesein, "Computed tomographic findings in subjects who died from respiratory disease in the National Lung Screening Trial", European Respiratory Journal, 2017; 49: 1601814.
B. D. de Vos, J. M. Wolterink, P. A. de Jong, T. Leiner, M. A. Viergever and I. Isgum, "ConvNet-based localization of anatomical structures in 3D medical images", IEEE Transactions on Medical Imaging, 2017; 36 (7): 1470-1481.
K. Murphy, N. E. van der Aa, S. Negro, F. Groenendaal, L. S. de Vries, M. A. Viergever, G. B. Boylan, M. J. N. L. Benders and I.Isgum, "Automatic quantification of ischemic injury on diffusion-weighted MRI of neonatal hypoxic ischemic encephalopathy", NeuroImage: Clinical, 2017; 14: 222-232.
P. Natarajan, J. C. Bis, L.F. Bielak, A.J. Cox, M. Dorr, M.F. Feitosa;, N. Franceschini, X. Guo, S-J. Hwang, A. Isaacs, M. A. Jhun,....I. Isgum, ....P.A. Peyser, C.J. O'Donnell, "Multiethnic exome-wide association study of subclinical atherosclerosis", Circulation Cardiovascular Genetics, 2016; 9 (6): 511-520.
A. A. A. Setio, F. Ciompi, G. Litjens, P. Gerke, C. Jacobs, S. van Riel, M. W. Wille, M. Naqibullah, C. I. Sánchez and B. van Ginneken, "Pulmonary nodule detection in CT images: false positive reduction using multi-view convolutional networks", IEEE Transactions on Medical Imaging, 2016; 35 (5): 1160-1169.
P. Maduskar, R. H. M. M. Philipsen, J. Melendez, E. Scholten, D. Chanda, H. Ayles, C. I. Sánchez and B. van Ginneken, "Automatic detection of pleural effusion in chest radiographs", Medical Image Analysis, 2016; 28: 22-32.
J. Melendez, B. van Ginneken, P. Maduskar, R. Philipsen, H. Ayles and C. I. Sánchez, "On Combining Multiple-Instance Learning and Active Learning for Computer-Aided Detection of Tuberculosis", IEEE Transactions on Medical Imaging, 2016; 35 (4): 1013-1024.
J. Melendez, C. I. Sánchez, R. H. H. M. Philipsen, P. Maduskar, R. Dawson, G. Theron, K. Dheda and B. van Ginneken, "An automated tuberculosis screening strategy combining X-ray-based computer-aided detection and clinical information", Nature Scientific Reports, 2016; 6: 25265.
G. Litjens, C. I. Sánchez, N. Timofeeva, M. Hermsen, I. Nagtegaal, I. Kovacs, C. de Hulsbergen-van Kaa, P. Bult, B. van Ginneken and J. van der Laak, "Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis", Nature Scientific Reports, 2016; 6: 26286.
M. J. J. P. van Grinsven, T. Theelen, L. Witkamp, J. van der Heijden, J. P. H. van de Ven, C. B. Hoyng, B. van Ginneken and C. I. Sánchez, "Automatic differentiation of color fundus images containing drusen or exudates using a contextual spatial pyramid approach", Biomedical Optics Express, 2016; 7 (3): 709-725.
M. J. J. P. van Grinsven, B. van Ginneken, C. B. Hoyng, T. Theelen and C. I. Sánchez., "Fast Convolutional Neural Network Training Using Selective Data Sampling: Application to Hemorrhage Detection in Color Fundus Images", IEEE Transactions on Medical Imaging, 2016; 35 (5): 1273-1284.
J. D. Hoffman, M. J. J. P. van Grinsven, C. Li, M. Brantley Jr, J. McGrath, A. Agarwal, W. K. Scott, S. G. Schwartz, J. Kovach, M. Pericak-Vance, C. I. Sánchez and J. L. Haines, "Genetic Association Analysis of Drusen Progression", Investigative Ophthalmology and Visual Science, 2016; 57 (4): 2225-2231.
K. Keunen, I. Isgum, B. van Kooij, P. Anbeek, I. van Haastert, C. Koopman-Esseboom, P. F. Stam, R. A. Nievelstein, M. A. Viergever, L. de Vries, G. Groenendaal and M. Benders, "Brain volumes at term-equivalent age in preterm infants: imaging biomarkers for neurodevelopmental outcome through early school age", The journal of Pediatrics, 2016; 172: 88-95.
S. A. M. Gernaat, I. Isgum, B. D. de Vos, R. A. P. Takx, D. A. Y. Afat, N. Rijnberg, D. E. Grobbee, Y. van der Graaf, P. A. de Jong, T. Leiner, H. J. G. D. van den Bongard, J. P. Pignol and H. M. Verkooijen, "Automatic coronary artery calcium scoring on radiotherapy planning CT scans of breast cancer patients: reproducibility and association with traditional cardiovascular risk factors", Plos One, 2016; 11 (12): e0167925.
A. M. den Harder, J. M. Wolterink, M. J. Willemink, A. M. R. Schilham, P. A. de Jong, R. P. J. Budde, H. M. Nathoe, I. Isgum and T. Leiner, "Submillisievert coronary calcium quantification using model-based iterative reconstruction: a within-patient analysis", European Journal of Radiology, 2016; 85 (11): 2152-2159.
S. W. van der Laan, T. Fall, A. Soumaré, A. Teumer, S. Sedaghat, J. Baumert, D. Zabaneh, J. van Setten, I. Isgum, T. E. Galesloot, J. Arpegård, P. Amouyel, S. Trompet, M. Waldenberger, M. Dörr, P. K. Magnusson, V. Giedraitis, A. Larsson, A. P. Morris, J. F. Felix, A. C. Morrison, N. Franceschini, J. C. Bis, M. Kavousi, C. O'Donnell, F. Drenos, V. Tragante, P. B. Munroe, R. Malik, M. Dichgans and E. al, "Cystatin C and cardiovascular disease: A Mendelian randomization study", Journal of the American College of Cardiology, 2016; 68 (9): 934-945.
K. J. Kersbergen, F. Leroy, I. Isgum, F. Groenendaal, L. S. de Vries, N. H. P. Claessens, I. C. van Haastert, P. Moeskops, C. Fischer, J. -. Mangin, M. A. Viergever, J. Dubois and M. J. N. L. Benders, "Relation between clinical risk factors, early cortical changes, and neurodevelopmental outcome in preterm infants", NeuroImage, 2016; 5 (142): 301-310.
N. H. P. Claessens, P. Moeskops, A. Buchmann, B. Latal, W. Knirsch, I. Scheer, I. Isgum, L. S. de Vries, M. J. N. L. Benders and M. von Rhein, "Delayed cortical gray matter development in neonates with severe congenital heart disease", Pediatric Research, 2016; 80 (5): 668-674.
J. M. Wolterink, T. Leiner, B. D. de Vos, R. W. van Hamersvelt, M. A. Viergever and I. Isgum, "Automatic coronary artery calcium scoring in cardiac CT angiography using paired convolutional neural networks", Medical Image Analysis, 2016; 34: 123-136.
P. Moeskops, M. A. Viergever, A. M. Mendrik, L. S. de Vries, M. J. N. L. Benders and I. Isgum, "Automatic segmentation of MR brain images with a convolutional neural network", IEEE Transactions on Medical Imaging, 2016; 35 (5): 1252-1261.
P. M. Lemmers, M. J. N. L. Benders, R. D'Ascenzo, J. Zethof, T. Alderliesten, K. J. Kersbergen, I. Isgum, L. S. de Vries, F. Groenendaal and F. van Bel, "Patent ductus arteriosus and brain volume.", Pediatrics, 2016; 137 (4): e2015309.
J. M. Wolterink, T. Leiner, B. D. de Vos, J. Coatrieux, B. M. Kelm, S. Kondo, R. A. Salgado, R. Shahzad, H. Shu, M. Snoeren, R. A. P. Takx, L. J. van Vliet, T. van Walsum, T. P. Willems, G. Yang, Y. Zheng, M. A. Viergever and I. Isgum, "An evaluation of automatic coronary artery calcium scoring methods with cardiac CT using the orCaScore framework", Medical Physics, 2016; 43 (5): 2361.
A. Vos, W. van Hecke, W. G. M. Spliet, R. Goldschmeding, I. Isgum, R. Kockelkoren, R. L. A. W. Bleys, W. P. T. M. Mali, P. A. de Jong and A. Vink, "Predominance of nonatherosclerotic internal elastic lamina calcification in the intracranial internal carotid artery", Stroke, 2016; 47 (1): 221-3.
M. J. Brouwer, L. S. de Vries, K. J. Kersbergen, N. E. van der Aa, A. J. Brouwer, M. A. Viergever, I. Isgum, K. S. Han, F. Groenendaal and M. J. N. L. Benders, "Effects of posthemorrhagic ventricular dilatation in the preterm infant on brain volumes and white matter diffusion variables at term-equivalent age", Journal of Pediatrics, 2016; 168: 41-49.e1.
M. Teussink, B. Cense, M. van Grinsven, B. Klevering, C. Hoyng and T. Theelen, "Impact of motion-associated noise on intrinsic optical signal imaging in humans with optical coherence tomography", Biomedical Optics Express, 2015; 6 (5): 1632-1647.
M. M. Teussink, M. B. Breukink, M. J. J. P. van Grinsven, C. B. Hoyng, B. J. Klevering, C. J. F. Boon, E. K. de Jong and T. Theelen, "OCT Angiography Compared to Fluorescein and Indocyanine Green Angiography in Chronic Central Serous Chorioretinopathy", Investigative Ophthalmology and Visual Science, 2015; 56 (9): 5229-5237.
S. J. van Riel, C. I. Sánchez, A. A. Bankier, D. P. Naidich, J. Verschakelen, E. T. Scholten, P. A. de Jong, C. Jacobs, E. van Rikxoort, L. Peters-Bax, M. Snoeren, M. Prokop, B. van Ginneken and C. Schaefer-Prokop, "Observer Variability for Classification of Pulmonary Nodules on Low-Dose CT Images and Its Effect on Nodule Management", Radiology, 2015; 277 (3): 863-871.
J. Melendez, B. van Ginneken, P. Maduskar, R. H. H. M. Philipsen, K. Reither, M. Breuninger, I. M. O. Adetifa, R. Maane, H. Ayles and C. I. Sánchez, "A Novel Multiple-Instance Learning-Based Approach to Computer-Aided Detection of Tuberculosis on Chest X-Rays", IEEE Transactions on Medical Imaging, 2015; 34 (1): 179-192.
R. Philipsen, P. Maduskar, L. Hogeweg, J. Melendez, C. I. Sánchez and B. van Ginneken, "Localized energy-based normalization of medical images: application to chest radiography", IEEE Transactions on Medical Imaging, 2015; 34 (9): 1965-75.
R. H. H. M. Philipsen, C. I. Sánchez, P. Maduskar, J. Melendez, L. Peters-Bax, J. G. Peter, R. Dawson, G. Theron, K. Dheda and B. van Ginneken, "Automated chest-radiography as a triage for Xpert testing in resource-constrained settings: a prospective study of diagnostic accuracy and costs", Nature Scientific Reports, 2015; 5.
M. J. J. P. van Grinsven, G. H. S. Buitendijk, C. Brussee, B. van Ginneken, C. B. Hoyng, T. Theelen, C. C. W. Klaver and C. I. Sánchez, "Automatic identification of reticular pseudodrusen using multimodal retinal image analysis", Investigative Ophthalmology and Visual Science, 2015; 56 (1): 633-639.
L. Hogeweg, C. I. Sánchez, P. Maduskar, R. Philipsen, A. Story, R. Dawson, G. Theron, K. Dheda, L. Peters-Bax and B. van Ginneken, "Automatic detection of tuberculosis in chest radiographs using a combination of textural, focal, and shape abnormality analysis", IEEE Transactions on Medical Imaging, 2015; 34 (12): 2429-2442.
P. Moeskops, M. J. N. L. Benders, K. J. Kersbergen, F. Groenendaal, L. S. de Vries, M. A. Viergever and I. Išgum, "Development of cortical morphology evaluated with longitudinal MR brain images of preterm infants", PLOS ONE, 2015; 10 (7): e0131552.
P. Moeskops, M. J. N. L. Benders, S. M. Chita, K. J. Kersbergen, F. Groenendaal, L. S. de Vries, M. A. Viergever and I. Išgum, "Automatic segmentation of MR brain images of preterm infants using supervised classification", NeuroImage, 2015; 118: 628-641.
M. J. Willemink, R. A. Takx, I. Išgum, H. J. de Koning, M. Oudkerk, W. P. Mali, R. P. Budde, T. Leiner, R. Vliegenthart and P. A. de Jong, "Prognostic value of heart valve calcifications for cardiovascular events in a lung cancer screening population", The International Journal of Cardiovascular Imaging, 2015; 31 (6): 1243-1249.
P. M. Jairam, P. A. de Jong, W. P. Mali, I. Isgum and Y. G. P. van der study-group., "Cardiovascular disease prediction: do pulmonary disease-related chest CT features have added value?", European Radiology, 2015; 25 (6): 1646-1654.
J.M. Wolterink, T. Leiner, R.A.P. Takx, M.A. Viergever and I. Isgum, "Automatic coronary calcium scoring in non-contrast-enhanced ECG-triggered cardiac CT with ambiguity detection", IEEE Transactions on Medical Imaging, 2015; 34 (9): 1867-1878.
J. van Setten, I. Isgum, S. Pechlivanis, V. Tragante, P. A. de Jong, J. Smolonska, M. Platteel, P. Hoffmann, M. Oudkerk, H. J. de Koning, M. M. Nöthen, S. Moebus, R. Erbel, K. H. Jöckel, M. A. Viergever, W. P. Mali and P. I. de Bakker, "Serum lipid levels, body mass index, and their role in coronary artery calcification: A polygenic analysis", Circulation: Cardiovascular Genetics, 2015; 8 (2): 327-333.
R. A. P. Takx, I. Isgum, M. J. Willemink, Y. van der Graaf, H. J. de Koning, R. Vliegenthart, M. Oudkerk, T. Leiner and P. A. de Jong, "Quantification of coronary artery calcium in non-gated CT to predict cardiovascular events in male lung cancer screening participants: Results of the NELSON Study", Journal of Cardiovascular Computed Tomography, 2015; 9 (1): 50-57.
R. A. Takx, R. Vliegenthart, F. A. Hoesein, I. Isgum, H. J. de Koning, W. P. Mali, C. M. van der Aalst, P. Zanen, J. W. Lammers, H. J. Groen, E. M. van Rikxoort, M. Schmidt, B. van Ginneken, M. Oudkerk, T. Leiner and P. A. de Jong, "Pulmonary function and CT biomarkers as risk factors for cardiovascular events in male lung cancer screening participants: the NELSON study", European Radiology, 2015; 25 (1): 65-71.
C. F. Buckens, Y. van der Graaf, H. M. Verkooijen, W. P. Mali, I. Isgum, C. P. Mol, H. J. Verhaar, R. Vliegenthart, M. Oudkerk, C. M. van Aalst, H. J. de Koning and P. A. de Jong, "Osteoporosis markers on low-dose lung cancer screening chest computed tomography scans predict all-cause mortality", European Radiology, 2015; 25 (1): 132-139.
I. Isgum, M. J. N. L. Benders, B. Avants, M. J. Cardoso, S. J. Counsell, E. F. Gomez, L. Gui, P. S. Hüppi, K. J. Kersbergen, A. Makropoulos, A. Melbourne, P. Moeskops, C. P. Mol, M. Kuklisova-Murgasova, D. Rueckert, J. A. Schnabel, V. Srhoj-Egekher, J. Wu, S. Wang, L. S. de Vries and M. A. Viergever, "Evaluation of automatic neonatal brain segmentation algorithms: the NeoBrainS12 challenge", Medical Image Analysis, 2015; 20 (1): 135-151.
N. Saksens, E. Kersten, J. M. M. Groenewoud, M. J. J. P. van Grinsven, J. P. H. van de Ven, C. I. Sánchez, T. Schick, S. Fauser, A. den Hollander, C. Hoyng and C. J. F. Boon, "Clinical characteristics of familial and sporadic age-related macular degeneration: differences and similarities", Investigative Ophthalmology and Visual Science, 2014; 55: 7085-7092.
P. Maduskar, L. Hogeweg, P. A. de Jong, L. Peters-Bax, R. Dawson, H. Ayles, C. I. Sánchez and B. van Ginneken, "Cavity contour segmentation in chest radiographs using supervised learning and dynamic programming", Medical Physics, 2014; 41 (7): 071912-1 - 071912-15.
J. Melendez, C. I. Sánchez, B. van Ginneken and N. Karssemeijer, "Improving mass candidate detection in mammograms via feature maxima propagation and local feature selection", Medical Physics, 2014; 41 (8): 81904.
C. A. Blok, K. J. Kersbergen, N. E. van der Aa, B. J. van Kooij, P. Anbeek, I. Isgum, L. S. de Vries, T. G. Krediet, F. Groenendaal, H. J. Vreman, F. van Bel and M. J. Benders, "Unmyelinated white matter loss in the preterm brain is associated with early increased levels of end-tidal carbon monoxide", PLoS One, 2014; 9 (3): e89061.
R. A. P. Takx, P. A. de Jong, T. Leiner, M. Oudkerk, H. J. de Koning, C. P. Mol, M. A. Viergever and I. Isgum, "Automated coronary artery calcification scoring in non-gated chest CT: Agreement and reliability", PLoS One, 2014; 9 (3): e91239.
M. J. N. L. Benders, N. E. van der Aa, M. Rok, H. L. van Straaten, I. Isgum, M. A. Viergever, F. Groenendaal, L. S. de Vries and F. van Bel, "Feasibility and safety of erythropoietin for neuroprotection after perinatal arterial ischemic stroke", The Journal of Pediatrics, 2014; 64 (3): 481-486.e2.
P. A. de Jong, W. E. Hellings, R. A. P. Takx, I. Isgum, J. A. van Herwaarden and W. P. Mali, "Computed tomography of aortic wall calcifications in aortic dissection patients", PLoS One, 2014; 9 (7): e102036.
R. W. van Hamersvelt, M. J. Willemink, R. A. P. Takx, A. L. M. Eikendal, R. P. J. Budde, T. Leiner, C. P. Mol, I. Isgum and P. A. de Jong, "Cardiac valve calcifications on low-dose unenhanced ungated chest computed tomography: interobserver and interexamination reliability, agreement and variability", European Radiology, 2014; 24 (7): 1557-1564.
F. A. A. M. Hossein, M. Schmidt, O. M. Mets, H. A. Gietema, J. -. J. Lammers, P. Zanen, H. J. de Koning, C. van der Aalst, M. Oudkerk, R. Vliegenthart, I. Isgum, M. Prokop, B. van Ginneken, E. M. van Rikxoort and P. A. de Jong, "Discriminating dominant computed tomography phenotypes in smokers without or with mild COPD", Respiratory Medicine, 2014; 108 (1): 136-143.
W. U. de Jong, P. A. de Jong, R. Vliegenthart, I. Isgum, J. -. J. Lammers, M. Oudkerk, C. van der Aalst, H. J. de Koning and F. A. M. Hoesein, "Association of COPD and smoking status with bone density and vertebral fractures in male lung cancer screening participants", Journal of Bone and Mineral Research, 2014; 29 (10): 2224-2229.
N. Gotovac, I. Isgum, M. A. Viergever, G. J. Biessels, J. Fajdic, B. K. Velthuis and M. Prokop, "Calcium at the carotid siphon as an indicator of internal carotid artery stenosis", European Radiology, 2013; 23 (6): 1478-1486..
M. J. J. P. van Grinsven, Y. T. E. Lechanteur, J. P. H. van de Ven, B. van Ginneken, C. B. Hoyng, T. Theelen and C. I. Sánchez, "Automatic Drusen Quantification and Risk Assessment of Age-related Macular Degeneration on Color Fundus Images", Investigative Ophthalmology and Visual Science, 2013; 54 (4): 3019-3027.
L. Hogeweg, C. I. Sánchez, J. Melendez, P. Maduskar, A. Story, A. Hayward and B. van Ginneken, "Foreign object detection and removal to improve automated analysis of chest radiographs", Medical Physics, 2013; 40 (7): 71901.
L. Hogeweg, C. I. Sánchez and B. van Ginneken, "Suppression of translucent elongated structures: applications in chest radiography", IEEE Transactions on Medical Imaging, 2013; 32 (11): 2099-2113.
O. M. Mets, M. Schmidt, C. F. Buckens, M. J. Gondrie, I. Isgum, M. Oudkerk, R. Vliegenthart, H. J. de Koning, C. M. van der Aalst, M. Prokop, J. W. Lammers, P. Zanen, F. A. Hoesein, W. P. Mali, B. van Ginneken, E. M. van Rikxoort and P. A. de Jong, "Diagnosis of chronic obstructive pulmonary disease in lung cancer screening Computed Tomography scans: independent contribution of emphysema, air trapping and bronchial wall thickening", Respiratory Research, 2013; 14: 59.
O. M. Mets, R. Vliegenthart, M. Gondrie, M. A. Viergever, M. Oudkerk, H. de Koning, W. P. T. M. Mali, M. Prokop, R. van Klaveren, Y. van der Graaf, C. Buckens, P. Zanen, J. -. Lammers, H. Groen, I. Isgum and P. de Jong, "Lung cancer screening CT-based prediction of cardiovascular events", JACC: Cardiovascular Imaging, 2013; 3 (8): 899-907.
J. van Setten, I. Isgum, J. Smolonska, S. Ripke, P. A. de Jong, M. Oudkerk, H. de Koning, J. -. J. Lammers, P. Zanen, H. J. M. Groen, H. M. Boezen, D. S. Postma, C. Wijmenga, M. A. Viergever, W. P. T. M. Mali and P. I. W. de Bakker, "Genome-wide association study of coronary and aortic calcification implicates risk loci for coronary artery disease and myocardial infarction", Atherosclerosis, 2013; 228 (2): 400-405.
K. J. Kersbergen, L. S. de Vries, B. J. M. van Kooij, I. Isgum, K. J. Rademaker, F. van Bel, P. S. Hüppi, J. Dubois, F. Groenendal and M. J. N. L. Benders, "The effect of hydrocortisone treatment for bronchopulmonary dysplasia on brain volumes in preterm infants", The Journal of Pediatrics, 2013; 163 (3): 666-71.e1.
P. M. Jairam, P. A. de Jong, W. P. T. M. Mali, I. Isgum, H. J. de Koning, C. van der Aalst, M. Oudkerk, R. Vliegenthart and Y. van der Graaf, "Impact of cardiovascular calcifications on the detrimental effect of continued smoking on cardiovascular risk in male lung cancer screening participants", PLoS One, 2013; 8 (6): e66484.
S. N. Verhagen, A. Rutten, M. F. Meijs, I. Isgum, M. -. Cramer, Y. van der Graaf and F. L. J. Visseren, "Relationship between myocardial bridges and reduced coronary atherosclerosis in patients with angina pectoris", International Journal of Cardiology, 2013; 167 (3): 883-888.
P. Anbeek, I. Isgum, B. J. M. van Kooij, C. P. Mol, K. J. Kersbergen, F. Groenendaal, M. A. Viergever, L. S. de Vries and M. J. N. L. Benders, "Automatic segmentation of eight tissue classes in neonatal brain MRI", PLoS One, 2013; 8 (12): e81895.
T. Tan, B. Platel, H. Huisman, C. I. Sánchez, R. Mus and N. Karssemeijer, "Computer Aided Lesion Diagnosis in Automated 3D Breast Ultrasound Using Coronal Spiculation", IEEE Transactions on Medical Imaging, 2012; 31 (5): 1034-1042.
C. I. Sánchez, M. Niemeijer, I. Išgum, A. V. Dumitrescu, M. S. A. Suttorp-Schulten, M. D. Abràmoff and B. van Ginneken, "Contextual computer-aided detection: Improving bright lesion detection in retinal images and coronary calcification identification in CT scans", Medical Image Analysis, 2012; 16 (1): 50-62.
L. Hogeweg, C. I. Sánchez, P. A. de Jong, P. Maduskar and B. van Ginneken, "Clavicle segmentation in chest radiographs", Medical Image Analysis, 2012; 16 (8): 1490 - 1502.
P. C. Jacobs, M. J. A. Gondrie, Y. van der Graaf, H. J. de Koning, I. Isgum, B. van Ginneken and W. P. T. M. Mali, "Coronary artery calcium can predict all-cause mortality and cardiovascular events on low-dose CT screening for lung cancer", American Journal of Roentgenology, 2012; 198 (3): 505-511.
K. Keunen, K. J. Kersbergen, F. Groenendaal, I. Isgum, L. S. de Vries and M. J. N. L. Benders, "Brain tissue volumes in preterm infants: prematurity, perinatal risk factors and neurodevelopmental outcome – A systematic review", The Journal of Maternal-Fetal and Neonatal Medicine, 2012; Suppl 1: 89-100.
O. M. Mets, I. Isgum, C. P. Mol, H. A. Gietema, P. Zanen, M. Prokop and P. A. de Jong, "Variation in quantitative CT air trapping in heavy smokers on repeat CT examinations", European Radiology, 2012; 22 (12): 2710-2717.
I. Isgum, M. Prokop, M. Niemeijer, M. A. Viergever and B. van Ginneken, "Automatic coronary calcium scoring in low-dose chest computed tomography", IEEE Transactions on Medical Imaging, 2012; 31 (12): 2322-2334.
O. M. Mets, P. Zanen, J. W. J. Lammers, I. Isgum, H. A. Gietema, B. van Ginneken, M. Prokop and P. A. de Jong, "Early identification of small airways disease on lung cancer screening CT: Comparison of current air trapping measures", Lung, 2012; 190: 629-633.
A. Rutten, I. Isgum, M. Prokop, "Calcium scoring with prospectively ECG-triggered CT: using overlapping datasets generated with MPR decreases inter-scan variability", European Journal of Radiology , 2011; 80 (1): 83-88.
C. I. Sánchez, M. Niemeijer, A. V. Dumitrescu, M. S. A. Suttorp-Schulten, M. D. Abràmoff and B. van Ginneken, "Evaluation of a Computer-Aided Diagnosis system for Diabetic Retinopathy screening on public data", Investigative Ophthalmology and Visual Science, 2011; 52: 4866-4871.
F. A. A. M. Hoesein, B. de Hoop, P. Zanen, H. Gietema, C. L. J. J. Kruitwagen, B. van Ginneken, I. Isgum, C. P. Mol, R. J. van Klaveren, A. E. Dijkstra, H. J. M. Groen, H. M. Boezen, D. S. Postma, M. Prokop and J. J. Lammers, "CT-quantified emphysema in male heavy smokers: association with lung function decline", Thorax, 2011; 66 (9): 782-787.
O. M. Mets, C. F. M. Buckens, P. Zanen, I. Isgum, B. van Ginneken, M. Prokop, H. A. Gietema, J. -. J. Lammers, R. Vliegenthart, M. Oudkerk, R. J. van Klaveren, H. J. de Koning, W. P. T. M. Mali and P. A. de Jong, "Identification of chronic obstructive pulmonary disease in lung cancer screening computed tomographic scans", JAMA, 2011; 306 (16): 1775-1781.
M. Niemeijer, B. van Ginneken, M. J. Cree, A. Mizutani, G. Quellec, C. I. Sánchez, B. Zhang, R. Hornero, M. Lamard, C. Muramatsu, X. Wu, G. Cazuguel, J. You, A. Mayo, Q. Li, Y. Hatanaka, B. Cochener, C. Roux, F. Karray, M. Garcia, H. Fujita and M. D. Abràmoff, "Retinopathy online challenge: automatic detection of microaneurysms in digital color fundus photographs", IEEE Transactions on Medical Imaging, 2010; 29 (1): 185-195.
P. C. Jacobs, I. Isgum, M. Gondrie, W. P. Mali, B. van Ginneken, M. Prokop and Y. van der Graaf, "Coronary artery calcification scoring in low-dose ungated CT screening for lung cancer: interscan agreement", AJR. American Journal of Roentgenology, 2010; 194 (5): 1244-1249.
P. C. Jacobs, M. Prokop, Y. van der Graaf, M. J. Gondrie, K. J. Janssen, H. J. de Koning, I. Isgum, R. J. van Klaveren, M. Oudkerk, B. van Ginneken and W. P. Mali, "Comparing coronary artery calcium and thoracic aorta calcium for prediction of all-cause mortality and cardiovascular events on low-dose non-gated computed tomography in a high-risk population of heavy smokers", Atherosclerosis, 2010; 209 (2): 455-462.
I. Isgum, A. Rutten, M. Prokop, M. Staring, S. Klein, J. P. W. Pluim, M. A. Viergever and B. van Ginneken, "Automated aortic calcium scoring on low-dose chest computed tomography", Medical Physics, 2010; 37 (2): 714-723.
E. M. van Rikxoort, I. Isgum, Y. Arzhaeva, M. Staring, S. Klein, M. A. Viergever, J. P. W. Pluim and B. van Ginneken, "Adaptive local multi-atlas segmentation: Application to the heart and the caudate nucleus", Medical Image Analysis, 2010; 14 (1): 39-49.
C. I. Sánchez, M. García, A. Mayo, M. I. López and R. Hornero, "Retinal image analysis based on mixture models to detect hard exudates", Medical Image Analysis, 2009; 13 (4): 650-658.
M. García, C. I. Sánchez, J. Poza, M. I. López and R. Hornero, "Detection of hard exudates in retinal images using a radial basis function classifier", Annals of Biomedical Engineering, 2009; 37 (7): 1448-1463.
M. García, C. I. Sánchez, M. I. López, D. Abásolo and R. Hornero, "Neural network based detection of hard exudates in retinal images", Computer Methods and Programs in Biomedicine, 2009; 93 (1): sep-19.
I. Isgum, M. Staring, A. Rutten, M. Prokop, M. A. Viergever and B. van Ginneken, "Multi-atlas-based segmentation with local decision fusion – application to cardiac and aortic segmentation in CT scans", IEEE Transactions on Medical Imaging, 2009; 28 (7): 1000-1010.
J. Poza, R. Hornero, J. Escudero, A. Fernández and C. I. Sánchez, "Regional analysis of spontaneous MEG rhythms in patients with Alzheimer’s disease using spectral entropies", Annals of Biomedical Engineering, 2008; 36 (1): 141-152.
C. I. Sánchez, R. Hornero, M. I. López, M. Aboy, J. Poza and D. Abásolo, "A novel automatic image processing algorithm for detection of hard exudates based on retinal image analysis", Medical Engineering and Physics, 2008; 30 (3): 350-357.
A. Rutten, I. Isgum and M. Prokop, "Coronary calcification: effect of small variation of scan starting position on Agatston, volume, and mass scores", Radiology, 2008; 246 (1): 90-98.
I. Isgum, A. Rutten, M. Prokop and B. van Ginneken, "Detection of coronary calcifications from computed tomography scans for automated risk assessment of coronary artery disease", Medical Physics, 2007; 34 (4): 1450-1461.
R. Hornero, D. Abásolo, N. Jimeno, C. I. Sánchez, J. Poza and M. Aboy, "Variability, regularity, and complexity of time series generated by schizophrenic patients and control subjects", IEEE Transactions on Biomedical Engineering, 2006; 53 (2): 210-218.
D. Abásolo, R. Hornero, P. Espino, J. Poza, C. I. Sánchez and R. de la Rosa, "Analysis of regularity in the EEG background activity of Alzheimer’s disease patients with Approximate Entropy", Clinical Neurophysiology, 2005; 116 (8): 1826-1834.
I. Isgum, B. van Ginneken, M. Olree, "Automatic detection of calcifications in the aorta from CT scans of the abdomen. 3D computer-aided diagnosis.", Academic Radiology, 2004; 11 (3): 247-257.
inproceedings
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C. Magg, M. A. ter Wee, G. S. Buijs, A. J. Kievit, D. A. Krap, J. G. G. Dobbe, G. J. Streekstra, L. Blankevoort, C. I. Sánchez, "Towards automation in non-invasive measurement of knee implant displacement", SPIE Medical Imaging, Image Processing, 2024; 12927: 169-175.A. R. Krishnan, K. Xu, T. Z. Li, C. Gao, L. W. Remedios, P. Kanakaraj, H. H. Lee, S. Bao, F. Maldonado, K. L. L. Sandler, I. Išgum, B. A. Landman, "Inter-vendor harmonization of CT reconstruction kernels using unpaired image translation", SPIE Medical Imaging, Image Processing, 2024; 12926: 341-350.
C. Gao, M. E. Kim, H. H. Lee, Q. Yang, N. Mohd Khairi, P. Kanakaraj, N. R. Newlin, D. B. Archer, A. L. Jefferson, W. D. Taylor, B. D. Boyd, L. L. Beason-Held, S. M. Resnick, Y. Huo, K. D. Van Schaik, K. G. Schilling, D. Moyer, I. Išgum, B. A. Landman, "Predicting age from white matter diffusivity with residual learning", SPIE Medical Imaging, Image Processing, 2024; 12926: 608-616.
H. Xu, N. R. Newlin, M. E. Kim, C. Gao, P. Kanakaraj, A. R. Krishnan, L. W. Remedios, N. M. Khairi, K. R. Pechman, D. B. Archer, T. J. Hohman, A. L. Jefferson, I. Išgum, Y. Huo, D. C. Moyer, K. G. Schilling, B. A. Landman, "Evaluation of mean shift, Combat, and CycleGAN for harmonizing brain connectivity matrices across sites", SPIE Medical Imaging, Image Processing, 2024; 12926: 493-504.
N. Hampe, S. G. M. Van Velzen, J. P. Aben, R. L. M. van Herten, C. Collet, I. Išgum, "Deep learning-based prediction of fractional flow reserve after invasive coronary artery treatment", SPIE Medical Imaging, Image Processing, 2024; 12926: 100-107.
L. Alvarez-Florez, J. Sander, M. Bourfiss, F. V. Y. Tjong, B. K. Velthuis, I. Išgum, "Deep Learning for Automatic Strain Quantification in Arrhythmogenic Right Ventricular Cardiomyopathy", Statistical Atlases and Computational Models of the Heart, 2023; 14507: 25-34.
M. Tafuro, G. E. Jansen, I. Išgum , "Temporally Consistent Segmentations from Sparsely Labeled Echocardiograms Using Image Registration for Pseudo-labels Generation", International Workshop on Advances in Simplifying Medical Ultrasound, 2023; 14337: 195–204.
R.L.M. van Herten, L. van Harten, N. Planken, I. Isgum, "Generative Adversarial Networks for Coronary CT Angiography Acquisition Protocol Correction with Explicit Attenuation Constraints", Medical Imaging with Deep Learning, 2023; 227: 1288-1303.
L. van Harten, R.L.M. van Herten, J. Stoker and I. Isgum, "Deformable Image Registration with Geometry-informed Implicit Neural Representations", Medical Imaging with Deep Learning, 2023; 227: 730-742.
D. Karkalousos, I. Isgum, H. Marquering, M.W. A. Caan, "MultiTask Learning for accelerated-MRI Reconstruction and Segmentation of Brain Lesions in Multiple Sclerosis", Medical Imaging with Deep Learning, 2023; 227: 991-1005.
S. Płotka, M.K. Grzeszczyk, R. Brawura-Biskupski-Samaha, P. Gutaj, M. Lipa, T. Trzciński, A. Sitek, "BabyNet: Residual Transformer Module for Birth Weight Prediction on Fetal Ultrasound Video", Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022: 350-359.
Z. Zhai, Y. Wang, B. D. de Vos, J. M.H. Noothout, N. Planken and I. Išgum, "Generative adversarial network for coronary artery plaque synthesis in coronary CT angiography", SPIE Medical Imaging, Image Processing, 2022.
M.D. Oudkerk Pool, B.D. de Vos, M.M. Winter, I. Isgum, "Deep Learning-Based Data-Point Precise R-Peak Detection in Single-Lead Electrocardiograms", IEEE Engineering in Medicine & Biology Society (EMBC), 2021; 43: 718-721.
L. van Harten, C. de Jonge, J. Stoker, I. Isgum, "Untangling the small intestine in 3D cine-MRI using deep stochastic tracking", Medical Imaging with Deep Learning (MIDL 2021), 2021.
M. Zreik, N. Hampe, T. Leiner, N. Khalili, J.M. Wolterink, M. Voskuil, M.A. Viergever, I. Išgum, "Combined analysis of coronary arteries and the left ventricular myocardium in cardiac CT angiography for detection of patients with functionally significant stenosis", SPIE Medical Imaging, Image Processing, 2021; 11596: 115961F.
J. M. H. Noothout, E. M. Postma, S. Boesveldt, B. D. de Vos, P. A. M. Smeets and I. Išgum, "Automatic segmentation of the olfactory bulbs in MRI", SPIE Medical Imaging, Image Processing, 2021; 11596: 115961J.
J. Sander, B. D. de Vos and I. Išgum, "Unsupervised super-resolution: creating high-resolution medical images from low-resolution anisotropic examples", SPIE Medical Imaging, Image Processing, 2021; 11596: 115960E.
S. Bruns, J. M. Wolterink, T. P. W. van den Boogert, J. P. Henriques, J. Baan, R. N. Planken and I. Išgum, "Automatic whole-heart segmentation in 4D TAVI treatment planning CT", SPIE Medical Imaging, Image Processing, 2021; 11596: 115960B.
N. Hampe, J. M. Wolterink, C. Collet, R. N. Planken and I. Išgum, "Graph Attention Networks for Segment Labeling in Coronary Artery Trees", SPIE Medical Imaging, Image Processing, 2021; 11596: 115961I.
S. G. M. van Velzen, B. D. de Vos, H. M. Verkooijen, T. Leiner, M. A. Viergever and I. Išgum, "Coronary artery calcium scoring: can we do better?", SPIE Medical Imaging, Image Processing, 2020; 11313: 113130G.
L. D. van Harten, J. M. Wolterink, J. J. C. Verhoeff and I. Išgum, "Exploiting clinically available delineations for CNN-based segmentation in radiotherapy treatment planning", SPIE Medical Imaging, Image Processing, 2020; 11313: 113131F.
T. F. A. van der Ouderaa, I. Išgum, W. B. Veldhuis and B. D. de Vos, "Deep group-wise variational diffeomorphic image registration", MICCAI workshop on Thoracic Image Analysis, 2020; 12502: 155-164.
L. D. van Harten, J. M. Wolterink, J. J. C. Verhoeff and I. Išgum, "Automatic online quality control of synthetic CTs", SPIE Medical Imaging, Image Processing, 2020; 11313: 113131M.
B. D. de Vos, B. H. M. van der Velden, J. Sander, K. G. A. Gilhuijs, M. Staring and I. Išgum, "Mutual information for unsupervised deep learning image registration", SPIE Medical Imaging, Image Processing, 2020; 11313: 113130R.
de Vente, Coen and Vos, Pieter and Pluim, Josien and Veta, Mitko, "Simultaneous detection and grading of prostate cancer in multi-parametric MRI", International Conference on Medical Imaging with Deep Learning--Extended Abstract Track, 2019.
N. Lessmann, J.M. Wolterink, M. Zreik, M.A. Viergever, B. van Ginneken, I. Išgum, "Vertebra partitioning with thin-plate spline surfaces steered by a convolutional neural network", Medical Imaging with Deep Learning (MIDL 2019), 2019.
B. Liefers, C. González-Gonzalo, C. Klaver, B. van Ginneken and C. I. Sánchez, "Dense Segmentation in Selected Dimensions: Application to Retinal Optical Coherence Tomography", Medical Imaging with Deep Learning, 2019; 102: 337-346.
M. S. Elmahdy, J. M. Wolterink, H. Sokooti, I. Išgum and M. Staring, "Adversarial optimization for joint registration and segmentation in prostate CT radiotherapy", Medical Image Computing and Computer Assisted Intervention (MICCAI 2019), Lecture Notes in Computer Science, 2019; 11769: 366-374.
N. Khalili, E. Turk, M. Zreik, M. A. Viergever, M. J. N. L. Benders and I. Išgum, "Generative adversarial network for segmentation of motion affected neonatal brain MRI", Medical Image Computing and Computer Assisted Intervention (MICCAI 2019), Lecture Notes in Computer Science, 2019; 11766: 320-328.
J. Fernandes, V. Alves, N. Khalili, M. J. N. L. Benders, I. Išgum, J. Pluim and P. Moeskops, "Convolutional Neural Network-based regression for quantification of brain characteristics using MRI", WorldCist: 7th World Conference on Information Systems and Technologies, 2019; 931: 577-586.
L. D. van Harten, J. M. H. Noothout, J. J. C. Verhoeff, J. M. Wolterink and I. Išgum, "Automatic segmentation of organs at risk in thoracic CT scans by combining 2D and 3D convolutional neural networks", Proc. of SegTHOR challenge at IEEE International Symposium on Biomedical Imaging, 2019.
B. H. van der Velden, B. D. de Vos, C. E. Loo, H. J. Kuijf, I. Išgum and K. G. A. Gilhuijs, "Response monitoring of breast cancer on DCE-MRI using convolutional neural network-generated seed points and constrained volume growing", SPIE Medical Imaging, Image Processing, 2019; 10950: 109500D.
S. Bruns, J. M. Wolterink, R. W. van Hamersvelt, M. Zreik, T. Leiner and I. Išgum, "Improving myocardium segmentation in cardiac CT angiography using spectral information", SPIE Medical Imaging, Image Processing, 2019; 10949: 109492M.
S. G. M. van Velzen, M. Zreik, N. Lessmann, M. A. Viergever, P. A. de Jong, H. M. Verkooijen and I. Išgum, "Direct prediction of cardiovascular mortality from low-dose chest CT using deep learning", SPIE Medical Imaging, Image Processing, 2019; 10949: 109490X.
J. Sander, B. D. de Vos, J. M. Wolterink and I. Išgum, "Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI", SPIE Medical Imaging, Image Processing, 2019; 10949: 1094919.
J. M. Wolterink, T. Leiner and I. Išgum, "Graph convolutional networks for coronary artery segmentation in cardiac CT angiography", Graph Learning in Medical Imaging (GLMI 2019), Lecture Notes in Computer Science, 2019; 11849: 62-69.
S. Bruns, J. M. Wolterink, R. W. van Hamersvelt, T. Leiner and I. Išgum, "CNN-based segmentation of the cardiac chambers and great vessels in non-contrast-enhanced cardiac CT", Medical Imaging with Deep Learning (MIDL 2019), 2019.
de Vente, Coen and Veta, Mitko and Razeghi, Orod and Niederer, Steven and Pluim, Josien and Rhode, Kawal and Karim, Rashed, "Convolutional neural networks for segmentation of the left atrium from gadolinium-enhancement MRI images", International Workshop on Statistical Atlases and Computational Models of the Heart, 2018: 348-356.
C. González-Gonzalo, B. Liefers, B. van Ginneken and C. I. Sánchez, "Improving weakly-supervised lesion localization with iterative saliency map refinement", Medical Imaging with Deep Learning, 2018.
J. M. Wolterink, T. Leiner and I. Išgum, "Blood vessel geometry synthesis using generative adversarial networks", Medical Imaging with Deep Learning (MIDL 2018), 2018.
J. M. H. Noothout, B. D. de Vos, J. M. Wolterink, T. Leiner and I. Išgum, "CNN-based landmark detection in cardiac CTA scans", Medical Imaging with Deep Learning (MIDL 2018), 2018.
J. M. Wolterink, T. Leiner, M. A. Viergever and I. Išgum, "Automatic segmentation and disease classification using cardiac cine MR images", Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges. STACOM 2017, 2018; 10663: 101-110.
N. Lessmann, B. van Ginneken and I. Išgum, "Iterative convolutional neural networks for automatic vertebra identification and segmentation in CT images", SPIE Medical Imaging, Image Processing, 2018: 1057408.
J. M. H. Noothout, B. D. de Vos, J. M. Wolterink and I. Išgum, "Automatic segmentation of thoracic aorta segments in low-dose chest CT", SPIE Medical Imaging, Image Processing, 2018; 10574: 105741S.
M. Zreik, R. W. van Hamersvelt, J. M. Wolterink, T. Leiner, M. A. Viergever and I. Išgum, "Automatic detection and characterization of coronary artery plaque and stenosis using a recurrent convolutional neural network in coronary CT angiography", Medical Imaging with Deep Learning (MIDL 2018), 2018.
N. Lessmann, B. van Ginneken, P. A. de Jong and I. Išgum, "Iterative fully convolutional neural networks for automatic vertebra segmentation", Medical Imaging with Deep Learning (MIDL 2018), 2018.
B. Liefers, F. G. Venhuizen, T. Theelen, C. Hoyng, B. van Ginneken and C. I. Sánchez, "Fovea Detection in Optical Coherence Tomography using Convolutional Neural Networks", Medical Imaging, 2017; 10133: 1013302.
B. D. de Vos, F. F. Berendsen, M. A. Viergever, M. Staring and I. Isgum, "End-to-end unsupervised deformable image registration with a convolutional neural network", Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support: Third International Workshop, DLMIA 2017, 2017: 204-212.
H. Sokooti, B. D. de Vos, F. Berendsen, B. P. F. Lelieveldt, I. Isgum and M. Staring, "Nonrigid image registration using multi-scale 3D convolutional neural networks", Medical Image Computing and Computer Assisted Intervention − MICCAI 2017: 20th International Conference, Quebec City, QC, Canada, September 11-13, 2017, Proceedings, Part 1, 2017; 10433: 232-239.
J. M. Wolterink, A. M. Dinkla, M. H. F. Savenije, P. R. Seevinck, C. A. T. van den Berg and I. Isgum, "Deep MR to CT synthesis using unpaired data", SASHIMI 2017: Simulation and Synthesis in Medical Imaging, 2017: 14023.
N. Khalili, P. Moeskops, N. H. P. Claessens, S. Scherpenzeel, E. Turk, R. de Heus, M. J. N. L. Benders, M. A. Viergever, J. P. W. Pluim and I. Išgum, "Automatic segmentation of the intracranial volume in fetal MR images", MICCAI Workshop on Fetal and InFant Image analysis (FIFI 2017), 2017.
J. Šprem, B. D. de Vos, P. A. de Jong, M. A. Viergever and I. Isgum, "Classification of coronary artery calcifications according to motion artifacts in chest CT using a convolutional neural network", SPIE Medical Imaging, 2017.
J. M. Wolterink, A. M. Dinkla, M. H. F. Savenije, P. R. Seevinck, C. A. T. van den Berg and I. Isgum, "MR-to-CT synthesis using cycle-consistent generative adversarial networks", Proc. Neural Inf. Process. Syst.(NIPS). 2017, 2017.
M. Zreik, T. Leiner, B. D. de Vos, R. W. van Hamersvelt, M. A. Viergever and I. Isgum, "Automatic segmentation of the left ventricle in cardiac CT angiography using convolutional neural networks", IEEE International Symposium on Biomedical Imaging, 2016: pp. 40-43.
P. Moeskops, J. M. Wolterink, B. H. M. van der Velden, K. G. A. Gilhuijs, T. Leiner, M. A. Viergever and I. Isgum, "Deep learning for multi-task medical image segmentation in multiple modalities", Medical Image Computing and Computer-Assisted Intervention, 2016; 9901: 478-486.
B. D. de Vos, M. A. Viergever, P. A. de Jong and I. Isgum, "Automatic slice identification in 3D medical images with a ConvNet regressor", Deep Learning and Data Labeling for Medical Applications: First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, MICCAI 2016, Athens, Greece, 2016: 161-169.
N. Lessmann, I. Isgum, A. A. A. Setio, B. D. de Vos, F. Ciompi, P. A. de Jong, M. Oudkerk, W. P. T. M. Mali, M. A. Viergever and B. van Ginneken, "Deep convolutional neural networks for automatic coronary calcium scoring in a screening study with low-dose chest CT", SPIE Medical Imaging, 2016; 9785: 978511.
I. Isgum, B. D. de Vos, J. M. Wolterink, D. Dey, D. S. Berman, M. Rubeaux, T. Leiner and P. J. Slomka, "Automatic detection of cardiovascular risk in CT attenuation correction maps in Rb-82 PET/CTs", SPIE Medical Imaging, 2016; 9784: 978405-1-978405-6.
B. D. de Vos, J. M. Wolterink, P. A. de Jong, M. A. Viergever and I. Isgum, "2D image classification for 3D anatomy localization; employing deep convolutional neural networks", SPIE Medical Imaging, 2016; 9784: 97841Y-1-97841Y-7.
B. D. de Vos, J. van Setten, P. A. de Jong, W. P. Mali, M. Oudkerk, M. A. Viergever and I. Isgum, "Genome-wide association study of coronary and aortic calcification in lung cancer screening CT", SPIE Medical Imaging, 2016; 9784: 97841L-1-97841L-6.
J. M. Wolterink, T. Leiner, M. A. Viergever and I. Isgum, "Dilated convolutional neural networks for cardiovascular MR segmentation in congenital heart disease", HVSMR 2016: MICCAI Workshop on Whole-Heart and Great Vessel Segmentation from 3D Cardiovascular MRI in Congenital Heart Disease, 2016; 10129: 95-102.
F. G. Venhuizen, B. van Ginneken, B. Bloemen, M. J. J. P. van Grinsven, R. Philipsen, C. Hoyng, T. Theelen and C. I. Sánchez, "Automated Age-Related Macular Degeneration Classification in OCT using Unsupervised Feature Learning", Medical Imaging, 2015; 9414.
K. Murphy, N. E. van der Aa, S. Negro, F. Groenendaal, L. S. de Vries, M. A. Viergever, M. J. N. L. Benders and I. Isgum, "Automatic segmentation of cerebral ischemic lesions in neonatal apparent diffusion coefficient maps", Brain Lesions (Brainles) workshop in conjuction with International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2015.
J. M. Wolterink, T. Leiner, M. A. Viergever and I. Isgum, "Automatic coronary calcium scoring in cardiac CT angiography using convolutional neural networks", Medical Image Computing and Computer-Assisted Intervention, 2015; 9349: 589-596.
B. D. de Vos, P. A. de Jong, J. M. Wolterink, R. Vliegenthart, G. V. F. Wielingen, M. A. Viergever and I. Isgum, "Automatic machine learning based prediction of cardiovascular events in lung cancer screening data", SPIE Medical Imaging, 2015; 9414: 94140D.
P. Moeskops, M. A. Viergever, M. J. N. L. Benders and I. Isgum, "Evaluation of an automatic brain segmentation method developed for neonates on adult MR brain images", SPIE Medical Imaging, 2015; 9413: 941315.
J. Melendez, C. I. Sánchez, R. H. H. M. Philipsen, P. Maduskar and B. van Ginneken, "Multiple-instance learning for computer-aided detection of tuberculosis", Medical Imaging, 2014; 9035: 90351J.
J. M. Wolterink, T. Leiner, R. A. P. Takx, M. A. Viergever and I. Isgum, "An automatic machine learning system for coronary calcium scoring in clinical non-contrast enhanced, ECG-triggered cardiac CT", SPIE Medical Imaging, 2014; 9035.
M. J. J. P. van Grinsven, Y. T. E. Lechanteur, J. P. H. van de Ven, B. van Ginneken, T. Theelen and C. I. Sánchez, "Automatic Age-related macular degeneration detection and staging", Medical Imaging, 2013; 8670: 86700M.
M. J. J. P. van Grinsven, A. Chakravarty, J. Sivaswamy, T. Theelen, B. van Ginneken and C. I. Sánchez, "A bag of words approach for discriminating between retinal images containing exudates or drusen", IEEE International Symposium on Biomedical Imaging, 2013: 1444-1447.
I. Fondon, M. J. J. P. van Grinsven, C. I. Sánchez and A. Saez, "Perceptually adapted method for optic disc detection on retinal fundus images", IEEE 26th International Symposium on Computer-Based Medical Systems (CBMS), 2013: 279-284.
B. van Ginneken, R. H. H. M. Philipsen, L. Hogeweg, P. Maduskar, J. C. Melendez, C. I. Sánchez, R. Maane, B. dei Alorse, U. d'Alessandro and I. M. O. Adetifa, "Automated Scoring of Chest Radiographs for Tuberculosis Prevalence Surveys: A Combined Approach", The Fifth International Workshop on Pulmonary Image Analysis, 2013.
P. Moeskops, M. J. N. L. Benders, P. C. Pearlman, K. J. Kersbergen, A. Leemans, M. A. Viergever and I. Isgum, "Assessment of quantitative cortical biomarkers in the developing brain of preterm infants", SPIE Medical Imaging, 2013; 8670: 867011.
S. M. Chita, M. J. N. L. Benders, P. Moeskops, K. J. Kersbergen, M. A. Viergever and I. Isgum, "Automatic segmentation of the preterm neonatal brain with MRI using supervised classification", SPIE Medical Imaging, 2013; 8669: 86693X-1-86693X-6.
V. Srhoj-Egekher, M. J. N. L. Benders, M. A. Viergever and I. Isgum, "Automatic neonatal brain tissue segmentation with MRI", SPIE Medical Imaging, 2013; 8669.
P. C. Vos, I. Isgum, J. M. Biesbroek, B. K. Velthuis and M. A. Viergever, "Combined pixel classification and atlas-based segmentation of the ventricular system in brain CT images", SPIE Medical Imaging, 2013.
P. C. Pearlman, I. Isgum, K. J. Kersbergen, M. J. N. L. Benders, M. A. Viergever and J. P. W. Pluim, "Implicit surface registration with surface-oriented anisotropic deformation field smoothing", IEEE International Symposium on Biomedical Imaging, 2013: 476-479.
J. Melendez, C. I. Sánchez, R. Hupse, B. van Ginneken and N. Karssemeijer, "Potential of a Standalone Computer-Aided Detection System for Breast Cancer Detection in Screening Mammography", IWDM '12: Proceedings of the 11th International Workshop on Breast Imaging, 2012; 7361: 682-689.
T. T. J. P. Kockelkorn, R. Ramos, J. Ramos, C. I. Sánchez, P. A. de Jong, C. Schaefer-Prokop, J. C. Grutters, B. van Ginneken and M. A. Viergever, "Interactive classification of lung tissue in CT scans by combining prior and interactively obtained training data: a simulation study", International Conference on Pattern Recognition, 2012: 105-108.
P. C. Pearlman, I. Isgum, K. J. Kersbergen, M. J. N. L. Benders, M. A. Viergever and J. P. W. Pluim, "Elastic Demons: Characterizing cortical development in neonates using an implicit surface registration", 2nd International MICCAI Workshop on Spatiotemporal Image Analysis for Longitudinal and Time-Series Image Data (STIA'12), 2012.
V. Srhoj-Egekher, M. J. N. L. Benders, K. J. Kersbergen, M. A. Viergever and I. Isgum, "Automatic segmentation of neonatal brain MRI using atlas based segmentation and machine learning approach", MICCAI Grand Challenge: Neonatal Brain Segmentation 2012 (NeoBrainS12), 2012.
C. Jacobs, C. I. Sánchez, S. C. Saur, T. Twellmann, P. A. de Jong and B. van Ginneken, "Computer-Aided Detection of Ground Glass Nodules in Thoracic CT images using Shape, Intensity and Context Features", Medical Image Computing and Computer-Assisted Intervention, 2011; 6893: 207-214.
I. Isgum, N. E. van der Aa, F. Groenendaal, L. S. de Vries, M. J. N. L. Benders and M. A. Viergever, "MRI-based delineation of perinatal arterial ischemic stroke", Image Analysis of Human Brain Development workshop, 14th International Conference on Medical Image Computing and Computer Assisted Intervention, 2011.
C. I. Sánchez, M. Niemeijer, M. S. A. Suttorp-Schulten, M. D. Abràmoff and B. van Ginneken, "Improving hard exudate detection in retinal images through a combination of local and contextual information", IEEE International Symposium on Biomedical Imaging, 2010: 5-8.
C. I. Sánchez, M. Niemeijer, M. D. Abràmoff and B. van Ginneken, "Active learning for an efficient training strategy of computer-aided diagnosis systems: application to diabetic retinopathy screening", Medical Image Computing and Computer-Assisted Intervention, 2010; 6363: 603-610.
I. Isgum, M. Prokop, P. C. Jacobs, M. J. Gondrie, W. P. Mali, M. A. Viergever and B. van Ginneken, "Automatic coronary calcium scoring in low-dose non-ECG-synchronized thoracic CT scans", SPIE Medical Imaging, 2010; 7624.
C. I. Sánchez, M. Niemeijer, T. Kockelkorn, M. D. Abràmoff and B. van Ginneken, "Active learning approach for detection of hard exudates, cotton wool spots, and drusen in retinal images", SPIE Medical Imaging, 2009; 7260: 72601I1-72601I8.
C. I. Sánchez, R. Hornero, A. Mayo and M. Garcia, "Mixture model-based clustering and logistic regression for automatic detection of microaneurysms in retinal images", SPIE Medical Imaging, 2009; 7260: 72601M1-72601M8.
M. García, C. I. Sánchez, M. I. López, A. Díez and R. Hornero, "Automatic detection of red lesions in retinal images using a multilayer perceptron neural network", Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2008; 2008: 5425-5428.
E. M. van Rikxoort, I. Isgum, M. Staring, S. Klein and B. van Ginneken, "Adaptive local multi-atlas segmentation: Application to heart segmentation in chest CT scans", SPIE Medical Imaging, 2008: 691407-1 - 691407-6.
M. García, R. Hornero, C. I. Sánchez, M. I. López and A. Díez, "Feature extraction and selection for the automatic detection of hard exudates in retinal images", Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007: 4969-4972.
J. Poza, G. Vecilla, R. Hornero, M. I. López, C. I. Sánchez and A. Díez, "TeleOftalWeb 3.0: Web-based ophthalmologic medical record", Telemedicine in Future Health, 2006.
C. I. Sánchez, A. Mayo, M. García, M. I. López and R. Hornero, "Automatic image processing algorithm to detect hard exudates based on mixture models", Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2006; 1: 4453-4456.
C. I. Sánchez, M. I. López, M. García, A. Mayo and R. Hornero, "Automated retinal image analysis in a diabetic retinopathy telescreening program", Telemedicine in Future Health, 2006.
M. García, C. I. Sánchez, A. Díez, M. I. López and R. Hornero, "Detection of hard exudates based on neural networks as a diagnostic aid in the screening for diabetic retinopathy", Telemedicine in Future Health, 2006.
I. Isgum, B. van Ginneken, A. Rutten and M. Prokop, "Automated coronary calcification detection and scoring", 4th International Symposium on Image and Signal Processing and Analysis, 2005: 127-132.
D. Abásolo, C. Gómez, J. Poza, M. García, C. I. Sánchez and M. López, "EEG background activity analysis in Alzheimer’s disease patients with sample entropy", International Conference on Computational Bioengineering, 2005: 1067-1076.
C. I. Sánchez, R. Hornero, M. I. López and J. Poza, "Retinal image analysis to detect and quantify lesions associated with diabetic retinopathy", Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2004; 3: 1624-1627.
R. Hornero, D. Abásolo, J. Poza, C. I. Sánchez, P. Espino and R. de la Rosa, "Use of wavelets packets to compare electroencephalogram signal (EEG) in patiens with Alzheimer’s disease and control subjects", International Workshop of Systems, Signals and Image Processing, 2004: 35-38.
R. Hornero, C. I. Sánchez and M. I. López, "Automated retinal image analysis in a teleophthalmology diabetic retinopathy screening program", Telemedicine Journal and e-Health, 2004.
I. Isgum, B. van Ginneken and M. Prokop, "A pattern recognition approach to automated coronary calcium scoring", International Conference on Pattern Recognition, 2004.
M. I. López, C. I. Sánchez and R. Hornero, "Retinal image analysis to detect and quantify lesions associated with diabetic retinopathy", Association for Research in Vision and Ophthalmology, 2003.
I. Isgum, B. van Ginneken and M. A. Viergever, "Automatic detection of calcifications in the aorta from abdominal CT scans", Computer Assisted Radiology and Surgery, 2003: 1037-1042.
M. Zreik, N. Hampe, T. Leiner, N. Khalili, J. M. Wolterink, M. Voskuil, M. A. Viergever and I. Išgum, "Combined analysis of coronary arteries and the left ventricular myocardium in cardiac CT angiography for detection of patients with functionally significant stenosis", SPIE Medical Imaging; 11596: 115961F.
abstracts
92TOTAL RESOURCES
E. R. Meulendijks, B. Fabrizi, S. Bruns, T. van den Boogert, R. Wesselink, W. J. van Boven, A. Driessen, H. Niessen, T. A.C. de Vries, E. Eringa, N. Planken, I. Isgum, D. Dey, S. P. Krul, R. Hoebe, J. R. de Groot, R. Al-Shama, "Epicardial Adipose Tissue Neutrophil Inflammation Relates to Severity but not to Recurrence of Atrial Fibrillation and is Reflected by Attenuation in CTA Scans", Heart Rhythm, 2023.Schwartz, Roy and Khalid, Hagar and Liakopoulos, Sandra and Ouyang, Yanling and de Vente, Coen and Gonzalo, Cristina González and Lee, Aaron Y and Egan, Catherine A and Sánchez, Clara and Tufail, Adnan, "A deep learning pipeline for the detection and quantification of drusen and reticular pseudodrusen on optical coherence tomography", Investigative Ophthalmology & Visual Science, 2022.
Lemij, Hans G and de Vente, Coen and Sánchez, Clara I and Cuadros, Jorge and Jaccard, Nicolas and Vermeer, Koen, "Glaucomatous features in fundus photographs of eyes with ‘Referable glaucoma’of a large population based labeled data set for training an Artificial Intelligence (AI) algorithm for glaucoma screening", Investigative Ophthalmology & Visual Science, 2022.
M.A. Molenaar, C.F. Coerkamp, J.P. Man, B.J. Bouma, I. Isgum, N.J. Verouden, J.L. Selder, S.A.J. Chamuleau, M.J. Schuuring, "The impact of valvular heart disease in patients referred for suspected coronary artery disease", EuroEcho , 2022.
C. de Vente, C. González-Gonzalo, E. F. Thee, M. van Grinsven, C. C. W. Klaver and C. I. Sánchez, "Making AI Transferable Across OCT Scanners from Different Vendors", Association for Research in Vision and Ophthalmology, 2021.
C. González-Gonzalo, F. Verbraak, R. O., Schlingemann, C. W. Klaver, A. Y. Lee, A. Tufail, C. I. Sánchez, "Trustworthy AI: Closing the Gap between Development and Integration of AI in Ophthalmology", European Association for the Study of Diabetes Eye Complications Study Group, 2021.
C. González-Gonzalo, E. F. Thee, B. Liefers, C. W. Klaver and C. I. Sánchez, "Deep learning for automated stratification of ophthalmic images: Application to age-related macular degeneration and color fundus images", European Society of Retina Specialists, 2021.
C. González-Gonzalo, E. F. Thee, B. Liefers, C. de Vente, C. C. W. Klaver and C. I. Sánchez, "Hierarchical curriculum learning for robust automated detection of low-prevalence retinal disease features: application to reticular pseudodrusen", Association for Research in Vision and Ophthalmology, 2021.
E.M. Postma, J.M.H. Noothout, W.M. Boek, T. Hummel, P.A.M. Smeets, I. Išgum, S. Boesveldt, "Applying olfactory bulb volume in the clinic: relating clinical outcome measures to olfactory bulb volume using convolutional neural networks", Association for Chemoreception Sciences, 2021.
C. de Vente, M. van Grinsven, S. De Zanet, A. Mosinska, R. Sznitman, C. Klaver and C. I. Sánchez, "Estimating Uncertainty of Deep Neural Networks for Age-related Macular Degeneration Grading using Optical Coherence Tomography", Association for Research in Vision and Ophthalmology, 2020.
B. Liefers, P. Taylor, C. González-Gonzalo, A. Tufail and C. I. Sánchez, "Achieving expert level performance in quantifying 13 distinctive features of neovascular age-related macular degeneration on optical coherence tomography", European Society of Retina Specialists, 2020.
C. González-Gonzalo, S. C. Wetstein, G. Bortsova, B. Liefers, B. van Ginneken and C. I. Sánchez, "Are adversarial attacks an actual threat for deep learning systems in real-world eye disease screening settings?", European Society of Retina Specialists, 2020.
A. Ardu, B. Liefers, C. de Vente, C. González-Gonzalo, C. Klaver and C. I. Sánchez, "Artificial Intelligence for the Classification and Quantification of Reticular Pseudodrusen in Multimodal Retinal Images", European Society of Retina Specialists, 2020.
M. D. Oudkerk Pool, B. D. de Vos, J. M. Wolterink, S. Blok, M. J. Schuuring, H. Bleijendaal, D. A. J. Dohmen, I. I. Tulevski, G. A. Somsen, B. J. M. Mulder, Y. Pinto, B. J. Bouma, I. Išgum and M. M. Winter, "Distinguishing sinus rhythm from atrial fibrillation on single-lead ECGs using a deep neural network", European Society of Cardiology Conference, 2020.
R. Gal, S. G. van Velzen, M. J. Emaus, D. H. van den Bongard, M. L. Gregorowitsch, E. L. Blezer, G. Sofie, N. Lessmann, M. G. Sattler, M. J. Hooning, A. J. Teske, J. J. Penninkhof, H. Meijer, J. P. Pignol, J. Verloop, I. Išgum, H. M. Verkooijen and B. S. Group, "The risk of cardiovascular disease in irradiated breast cancer patients: The role of cardiac calcifications and adjuvant treatment", European Journal of Cancer, 2020.
D. Valkenburg, E. Runhart, B. Liefers, S. Lambertus, C. I. Sánchez, F. P. Cremers, B. Nathalie M and C. C. B. Hoyng, "Familial discordance in disease phenotype in siblings with Stargardt disease", Association for Research in Vision and Ophthalmology, 2019.
H. van Zeeland, J. Meakin, B. Liefers, C. González-Gonzalo, A. Vaidyanathan, B. van Ginneken, C. C. W. Klaver and C. I. Sánchez, "EyeNED workstation: Development of a multi-modal vendor-independent application for annotation, spatial alignment and analysis of retinal images", Association for Research in Vision and Ophthalmology, 2019.
B. Liefers, J. Colijn, C. González-Gonzalo, A. Vaidyanathan, H. van Zeeland, P. Mitchell, C. Klaver and C. I. Sánchez, "Prediction of areas at risk of developing geographic atrophy in color fundus images using deep learning", Association for Research in Vision and Ophthalmology, 2019.
C. González-Gonzalo, B. Liefers, A. Vaidyanathan, H. van Zeeland, C. C. W. Klaver and C. I. Sánchez, "Opening the “black box”? of deep learning in automated screening of eye diseases", Association for Research in Vision and Ophthalmology, 2019.
J. Engelberts, C. González-Gonzalo, C. I. Sánchez and M. J. van Grinsven, "Automatic Segmentation of Drusen and Exudates on Color Fundus Images using Generative Adversarial Networks", Association for Research in Vision and Ophthalmology, 2019.
M. Froeling, L. Schlaffke, M. Rohm, I. Išgum, H. Kan and J. M. Wolterink, "Evaluation of input data and UNet based convolutional network architectures for automated muscle annotation in 2D and 3D", International Society for Magnetic Resonance in Medicine, 27th Annual Meeting & Exhibition, 2019.
N. Khalili, N. Lessmann, E. Turk, M. A. Viergever, M. J. N. L. Benders and I. Išgum, "Brain tissue segmentation in fetal MRI using convolutional neural networks with simulated intensity inhomogeneities", International Society for Magnetic Resonance in Medicine, 27th Annual Meeting & Exhibition, 2019.
M.N. Cizmeci, N. Khalili, I. Išgum, N. Claessens, F. Groenendaal, D. Liem, A. Heep, I. B. Fernandez, I. van Straaten, G. van Wezel-Meijler, E. van ‘t Verlaat, A. Whitelaw, M.J.N.L. Benders, L.S. de Vries and ELVIS study group, "Timing of intervention for posthemorrhagic ventricular dilatation: effect on brain injury and brain volumes on term-equivalent age MRI", Pediatric Academic Societies (PAS) Meeting 2018, 2019.
S. G. M. van Velzen, J. G. Terry, B. D. de Vos, N. Lessmann, S. Nair, A. Correa, H. M. V. J. Carr and I. Išgum, "Automatic prediction of coronary heart disease events using coronary and thoracic aorta calcium among African Americans in the Jackson Heart study", Radiological Society of North America, 105th Annual Meeting, 2019.
S. G. M. van Velzen, N. Lessmann, M. J. Emaus, H. van den Bongard, H. M. Verkooijen and I. Išgum, "Deep learning for calcium scoring in radiotherapy treatment planning CT scans in breast cancer patients", Radiological Society of North America, 105th Annual Meeting, 2019.
P. Moeskops, B. D. de Vos, W. B. Veldhuis, A. M. May, S. Kurk, M. Koopman, P. A. de Jong, T.Leiner and I. Išgum, "Automatic quantification of 3D body composition from abdominal CT with an ensemble of convolutional neural networks", Radiological Society of North America, 105th Annual Meeting, 2019.
J. M. Wolterink, A. Mukhopadhyay, T. Leiner, T. Vogl, A. Bucher and I. Isgum, "Generative Adversarial Networks (GANs): a primer for radiologists", Radiological Society of North America, 105th Annual Meeting, 2019.
J. M. H. Noothout, B. D. de Vos, J. M. Wolterink, R. A. P. Takx, T. Leiner and I. Išgum, "Deep learning for automatic landmark localization in CTA for transcatheter aortic valve implantation", Radiological Society of North America, 105th Annual Meeting, 2019.
A. M. Dinkla, J. M. Wolterink, M. Maspero, M. H. F. Savenije, J. J. C. Verhoeff, I. Išgum, P. R. Seevinck, J. J. W. Lagendijk and C. A. T. van den Berg, "Dosimetric evaluation of deep learning based synthetic-CT generation for MR-only brain radiotherapy", ESTRO , 2018.
A. M. den Harder, J. M. Wolterink, P. A. de Jong, M. C. H. de Groot, R. P. J. Budde, I. Išgum, S. Haijtjema, I. E. Hoefer and T. Leiner, "Basic hematological biomarkers are associated with coronary calcifications", Annual Meeting of the European Society of Radiology, 2018.
R. W. van Hamersvelt, M. Zreik, M. Voskuil, I. Išgum and T. Leiner, "Deep learning-based analysis of the left ventricular myocardium in coronary CTA images improves specificity for detection of functionally significant coronary artery stenosis", European Congress of Radiology (ECR), 2018.
J. M. Wolterink, I. Išgum, E. Bennink, V. Huang, M. A. Viergever and T. Leiner, "Fully automatic segmentation of the renal cortex and medulla in contrast-enhanced abdominal CT using deep learning", 12th Netherlands Heart Days, 2018.
A. M. Dinkla, J. M. Wolterink, M. Maspero, M. H. F. Savenije, J. J. C. Verhoeff, I. Išgum, P. R. Seevinck, J. J. W. Lagendijk and C. A. T. van den Berg, "CT synthesis for MR-only brain radiotherapy treatment planning using convolutional neural networks", International Society for Magnetic Resonance in Medicine, 26th Annual Meeting & Exhibition, 2018.
A. Schreuder, C. Jacobs, N. Lessmann, E. T. Scholten, I. Išgum, M. Prokop, C. M. Schaefer-Prokop and B. van Ginneken, "Improved lung cancer and mortality prediction accuracy using survival models based on semi-automatic CT image measurements", World Conference on Lung Cancer, 2018.
F. G. Venhuizen, S. Schaffhauser, V. Schreur, B. Liefers, B. van Ginneken, C. B. Hoyng, T. Theelen, E. K. de Jong and C. I. Sánchez, "Fully automated detection of hyperreflective foci in optical coherence tomography", Association for Research in Vision and Ophthalmology, 2017.
B. Liefers, F. G. Venhuizen, V. Schreur, B. van Ginneken, C. Hoyng, T. Theelen and C. I. Sánchez, "Automatic detection of the foveal center in optical coherence tomography", Association for Research in Vision and Ophthalmology, 2017.
J. J. Gomez, C. I. Sánchez, B. Liefers, F. G. Venhuizen, G. Fatti, A. Morilla-Grasa, Y. Cartagena, A. H. Cabarcos, A. Santos, M. J. Ledesma-Carbayo and A. Anton-Lopez, "Automated Analysis of Retinal Images for detection of Glaucoma based on Convolutional Neural Networks", Association for Research in Vision and Ophthalmology, 2017.
J. M. Wolterink, I. Isgum, M. A. Viergever and T. Leiner, "Cardiovascular MR image segmentation in congenital heart disease using a dilated convolutional neural network", Society of Cardiovascular Computed Tomography, 12th Annual Scientific Meeting, 2017.
M. Zreik, N. Lessmann, R. van Hamersvelt, J. Wolterink, M. Voskuil, M. A. Viergever, T. Leiner and I. Isgum, "Deep learning analysis of the left ventricular myocardium in cardiac CT images enables detection of functionally significant coronary artery stenosis regardless of coronary anatomy", Radiological Society of North America, 103rd Annual Meeting, 2017.
J. M. Wolterink, T. Leiner, M. A. Viergever and I. Isgum, "An adversarial deep learning approach to coronary CT radiation reduction", Society of Cardiovascular Computed Tomography, 12th Annual Scientific Meeting, 2017.
A. M. den Harder, J. M. Wolterink, P. A. de Jong, M. C. H. de Groot, I. Isgum, W. B. Veldhuis, S. Haijtema, I. E. Hoefer and T. Leiner, "Towards understanding the role of the hematological system in the pathophysiology of coronary calcifications: A cohort study", Society of Cardiovascular Computed Tomography, 12th Annual Scientific Meeting, 2017.
R. van Hamersvelt, M. Zreik, N. Lessmann, J. Wolterink, M. Voskuil, M. A. Viergever, T. Leiner and I. Isgum, "Improving specificity of coronary CT angiography for the detection of functionally significant coronary artery disease: A deep learning approach", Radiological Society of North America, 103rd Annual Meeting, 2017.
N. Lessmann, B. van Ginneken, P. A. de Jong, W. B. Veldhuis, M. A. Viergever and I. Isgum, "Deep learning analysis for automatic calcium scoring in routine chest CT", Radiological Society of North America, 103rd Annual Meeting, 2017.
B. D. de Vos, N. Lessmann, P. A. de Jong, M. A. Viergever and I. Isgum, "Direct coronary artery calcium scoring in low-dose chest CT using deep learning analysis", Radiological Society of North America, 103rd Annual Meeting, 2017.
F. G. Venhuizen, M. J. J. P. van Grinsven, B. van Ginneken, C. B. Hoyng, T. Theelen and C. I. Sánchez, "Fully automated quantification of intraretinal cysts in 3D optical coherence tomography", Association for Research in Vision and Ophthalmology, 2016.
B. Liefers, V. Schreur, T. Theelen and C. I. Sánchez, "Registration and grading of micro-aneurysms in Fluorescein Angiography and OCT Angiography", 4th International Congress on OCT Angiography and Advances in OCT, 2016.
M. J. J. P. van Grinsven, F. G. Venhuizen, B. van Ginneken, C. B. Hoyng, T. Theelen and C. I. Sánchez, "Automatic detection of hemorrhages on color fundus images using deep learning", Association for Research in Vision and Ophthalmology, 2016.
A. M. den Harder, J. M. Wolterink, M. J. Willemink, A. M. R. Schilham, P. A. de Jong, R. P. J. Budde, H. M. Nathoe, I. Isgum and T. Leiner, "Low-dose coronary calcium scoring with model-based iterative reconstruction", Society of Cardiovascular Computed Tomography, 11th Annual Scientific Meeting, 2016.
F. M. Hoesein, E. Pompe, D. A. Lynch, N. Lessmann, J. W. J. Lammers, I. Isgum and P. A. de Jong, "Computed tomographic findings are associated with respiratory mortality in the National Lung Screening Trial", Radiology Society of North America, 102nd Annual Meetin, 2016.
F. G. Venhuizen, M. B. Breukink, B. van Ginneken, M. J. J. P. van Grinsven, B. Bloemen, C. B. Hoyng, T. Theelen, C. J. F. Boon and C. I. Sánchez, "Automated Quantification of Subretinal Fluid in Central Serous Chorioretinopathy in 3D Optical Coherence Tomography Images", Association for Research in Vision and Ophthalmology, 2015.
F. G. Venhuizen, M. J. van Grinsven, C. B. Hoyng, T. Theelen, B. van Ginneken and C. I. Sánchez, "Vendor Independent Cyst Segmentation in Retinal SD-OCT Volumes using a Combination of Multiple Scale Convolutional Neural Networks", Medical Image Computing and Computer-Assisted Intervention, 2015.
C. I. Sánchez, S. Lambertus, B. Bloemen, N. Bax, F. G. Venhuizen, M. J. J. P. van Grinsven, B. van Ginneken, T. Theelen and C. Hoyng, "Automatic quantification of geographic atrophy in fundus autofluorescence images of Stargardt patients", Association for Research in Vision and Ophthalmology, 2015.
P. Maduskar, I. Adetifa, J. van den Hombergh, E. Leroy-Terquem, A. Fasan-Odunsi, C. I. Sánchez, U. d'Alessandro and B. van Ginneken, "Computerized Reading of Chest Radiographs in The Gambia National Tuberculosis Prevalence Survey: Retrospective Comparison with Human Experts", Union World Conference on Lung Health, 2015.
R. H. Philipsen, C. I. Sánchez, P. Maduskar, J. Melendez, B. van Ginneken and W. J. Lew, "Objective Computerized Chest Radiography Screening to Detect Tuberculosis in the Philippines", Union World Conference on Lung Health, 2015.
M. J. J. P. van Grinsven, F. G. Venhuizen, B. van Ginneken, C. B. Hoyng, T. Theelen and C. I. Sánchez, "Automatic detection of eye diseases using automated color fundus image analysis", Association for Research in Vision and Ophthalmology, 2015.
N. Lessmann, I. Isgum, S. Lam, J. Mayo, P. A. de Jong, M. A. Viergever and B. van Ginneken, "Automatic coronary calcium scoring and cardiovascular risk estimation in the Pan-Canadian lung cancer screening trial", Radiology Society of North America, 101th Annual Meeting, 2015.
P. Moeskops, N. C. A'Campo, M. J. N. L. Benders, L. S. de Vries, M. A. Viergever and I. Isgum, "Automatic whole brain segmentation of MR brain images of preterm infants and adults using supervised classification", EEE ISBI NeatBrainS15 workshop, 2015.
J. M. Wolterink, T. Leiner, M. J. Willemink, M. A. Viergever and I. Isgum, "The impact of iterative reconstruction on detectability and quantification of calcifications in CT coronary calcium scoring: Individual lesion-by-lesion comparison", Radiology Society of North America, 101th Annual Meeting, 2015.
J. Šprem, B. D. de Vos, R. Vliegenthart, M. A. Viergever, P. A. de Jong and I. Isgum, "Increasing the Interscan Reproducibility of Coronary Calcium Scoring by Partial Volume Correction in Low-Dose non-ECG Synchronized CT: Phantom Study", Radiology Society of North America, 2015.
R. H. H. M. Philipsen, P. Maduskar, L. Hogeweg, J. Melendez, C. I. Sánchez and B. van Ginneken, "Robust Computer-Aided Detection of Tuberculosis in Chest Radiographs Using Energy Normalization", Annual Meeting of the Radiological Society of North America, 2014.
M. J. J. P. van Grinsven, G. H. S. Buitendijk, C. Brussee, B. van Ginneken, T. Theelen, C. C. W. Klaver and C. I. Sánchez, "Automatic detection of reticular drusen using multimodal retinal image analysis", Association for Research in Vision and Ophthalmology, 2014.
P. Moeskops, M. J. N. L. Benders, A. Buchmann, B. Latal, W. Knirsch, L. S. de Vries, C. Hagmann, I. Isgum and M. V. Rhein, "Cortical morphology in infants with congenital heart disease pre- and post-surgery", Pediatric Academic Societies Annual Meeting, 2014.
J. M. Wolterink, M. J. Willemink, R. A. P. Takx, M. Prokop, J. de Mey, M. Das, P. A. de Jong, R. P. J. Budde, A. M. R. Schilham, R. L. A. W. Bleys, N. Buls, J. E. Wildberger, M. A. Viergever, I. Isgum and T. Leiner, "Differences in coronary artery calcification scores obtained with different CT scanners are not software related", Society of Cardiovascular Computed Tomography, 9th Annual Scientific Meeting, 2014.
M. L. Tataranno, P. Moeskops, L. S. de Vries, K. J. Kersbergen, F. Groenendaal, L. G. M. van Rooij, M. C. Toet, G. Buonocore, I. Isgum and M. J. N. L. Benders, "Early brain activity and cortical development In preterm infants", Archives of Disease in Childhood, 2014.
N. H. P. Claessens, K. J. Kersbergen, F. Leroy, P. Moeskops, I. Isgum, M. A. Viergever, F. Groenendaal, L. S. de Vries, J. Dubois and M. J. N. L. Benders, "Maturational changes In cortical folding In extremely preterm infants", Archives of Disease in Childhood, 2014.
N. Gotovac, I. Isgum, B. K. Velthuis, M. A. Viergever, J. Fajdic and M. Prokop, "Positive calcium scores in the carotid arteries indicate carotid bifurcation stenosis", European Congres of Radiology, 2014.
M. Teussink, M. van Grinsven, B. Cense, C. Hoyng, J. Klevering and T. Theelen, "Functional optical coherence tomography with a commercial device – a pilot study", Association for Research in Vision and Ophthalmology, 2013.
P. Moeskops, I. Isgum, K. J. Kersbergen, F. Groenendaal, L. S. de Vries, M. A. Viergever and M. J. N. L. Benders, "Quantitative evaluation of cortical development in serial MR images of preterm infants", Pediatric Academic Societies Annual Meeting, 2013.
J. M. Wolterink, T. Leiner, P. A. de Jong, M. A. Viergever and I. Isgum, "Automatic coronary calcium scoring in ECG-triggered cardiac CT", Radiology Society of North America, 99th Annual Meeting, 2013.
C. Coviello, F. Groenendaal, I. Isgum, V. P. Carnielli, K. J. Kersbergen, B. J. van Kooij, B. Peels, P. Moeskops, M. A. Viergever, L. S. de Vries and M. J. N. L. Benders, "Effects of early nutrition on growth and brain volumes in preterm infants", Pediatric Academic Societies Annual Meeting, 2013.
B. Platel, T. Welte, R. Mus, R. Mann, C. I. Sánchez, H. Hahn and N. Karssemeijer, "Automated Evaluation of an Ultrafast MR Imaging Protocol for the Characterization of Breast Lesions", Annual Meeting of the Radiological Society of North America, 2012.
J. Melendez, C. I. Sánchez, B. van Ginneken and N. Karssemeijer, "Detection of breast carcinomas potentially missed during screening by means of a standalone CAD system", Annual Meeting of the Radiological Society of North America, 2012.
M. J. J. P. van Grinsven, J. P. H. van de Ven, Y. T. E. Lechanteur, B. van Ginneken, C. B. Hoyng, T. Theelen and C. I. Sánchez, "Automatic Drusen Detection and Quantification for Diagnosis of Age-Related Macular Degeneration", Association for Research in Vision and Ophthalmology, 2012.
M. J. J. P. van Grinsven, B. van Ginneken and C. I. Sánchez, "Web-based workstation for the analysis of color fundus images", ISBI Medical Image Analysis Workshop, 2012.
B. van Ginneken, L. Hogeweg, P. Maduskar, L. Peters-Bax, R. Dawson, K. Dheda, H. Ayles, J. Melendez and C. I. Sánchez, "Performance of inexperienced and experienced observers in detection of active tuberculosis on digital chest radiographs with and without the use of computer-aided diagnosis", Annual Meeting of the Radiological Society of North America, 2012.
K. Keunen, K. J. Kersbergen, I. Isgum, B. J. M. van Kooij, F. Groenendaal, P. Anbeek, M. A. Viergever, I. C. van Haastert, L. S. de Vries and M. J. N. L. Benders, "Outcome in preterm infants is associated with regional brain volumes at term equivalent age", Pediatric Academic Society Annual Meeting, 2012.
O. M. Mets, I. Isgum, C. P. Mol, H. A. Gietema, P. Zanen, M. Prokop and P. A. de Jong, "Interscan variability of quantitative computed tomography air trapping measures in low-dose chest CT", Annual Meeting of the European Society of Thoracic Imaging, 2012.
K. Keunen, K. J. Kersbergen, B. J. M. van Kooij, I. Isgum, P. Anbeek, M. Rast, M. A. Viergever, L. S. de Vries, F. Groenendaal and M. J. N. L. Benders, "Perinatal risk factors affecting cerebellar and ventricular volumes in preterm infants", Pediatric Academic Society Annual Meeting, 2012.
O. M. Mets, P. Zanen, I. Isgum, H. A. Gietema, B. van Ginneken, M. Prokop and P. A. de Jong, "What is the best quantitative Computed Tomographic (CT) air trapping method that corrects for emphysema severity?", Annual Meeting of the European Society of Thoracic Imaging, 2011.
O. M. Mets, P. Zanen, J. W. J. Lammers, I. Isgum, H. A. Gietema, B. van Ginneken, M. Prokop and P. A. de Jong, "Computed Tomographic diagnosis of air trapping in non- or mildly obstructed smokers", European Respiratory Society, Annual Congress, 2011.
J. van Setten, I. Isgum, R. J. van Klaveren, P. A. de Jong, M. A. Viergever, C. Wijmenga, W. P. Mali and P. I. W. de Bakker, "Multivariate association analysis of arterial calcification in the NELSON study", European Human Genetics Conference, 2011.
N. E. van der Aa, I. Isgum, F. Groenendaal, M. A. Viergever, L. S. de Vries and M. J. N. L. Benders, "Automatic segmentation of perinatal arterial ischemic stroke volume", 52nd Annual Meeting of the European Society for Paediatric Research, 2011.
B. van Kooij, F. Groenendaal, I. Isgum, K. Kersbergen, P. Anbeek, L. de Vries and M. Benders, "Indefinite gray-white matter border on MRI at term equivalent age in preterm infants with white matter injury", 52nd Annual Meeting of the European Society for Paediatric Research, 2011.
I. Isgum, P. A. de Jong, W. P. Mali, B. van Ginneken, M. Prokop and M. A. Viergever, "Automatic coronary calcium scoring in low-dose non-ECG synchronized chest computed tomography (CT) scans from a lung cancer screening trial", Radiology Society of North America, 97th Annual Meeting, 2011.
O. M. Mets, C. M. Buckens, P. Zanen, I. Isgum, M. Prokop and P. A. de Jong, "Development and validation of a diagnostic model for airflow limitation in heavy smokers by using quantitative computed tomography", Radiologiy Society of North America, 97th Annual Meeting, 2011.
N. Gotovac, I. Isgum, B. K. Velthuis, M. A. Viergever, J. Fajdic and M. Prokop, "Feasibility of calcium scoring of intracranial arteries as a measure of arteriosclerosis in stroke patients", European Congres of Radiology, 2011.
I. Isgum, B. van Ginneken, P. C. Jacobs, M. J. Gondrie, W. P. T. M. Mali and M. Prokop, "Automatic determination of cardiovascular risk from thoracic CT scans using a coronary calcium atlas", Radiological Society of North America, 95th Annual Meeting, 2009.
B. van Ginneken, K. Murphy, E. M. van Rikxoort, I. Isgum, B. de Hoop, M. Prokop, P. de Jong and H. Gietema, "Quantification of emphysema and small airway disease in COPD patients from lobar analysis of volumetric inspiration and expiration thoracic CT scans", Radiological Society of North America, 95th Annual Meeting, 2009.
I. Isgum, P. C. A. Jacobs, M. Gondrie, B. van Ginneken, M. Oudkerk, W. P. T. M. Mali, Y. van der Graaf and M. Prokop, "Cardiovascular risk assessment in lung cancer screening scans: do coronary and aortic calcium scores yield comparable risks for individual subjects?", European Congres of Radiology, 2009.
I. Isgum, R. van 't Klooster, P. J. H. de Koning, F. Jabi, K. DeMarco, J. H. C. Reiber and R. J. van der Geest, "Automatic detection of atherosclerotic carotid plaque from combined magnetic resonance angiography and vessel wall images", European Congres of Radiology, 2008.
I. Isgum, A. Rutten, M. Prokop and B. van Ginneken, "Automated calcium scoring in the aorta in low dose non-contrast-enhanced CT scans of the thorax", Radiological Society of North America, 93th Annual Meeting, 2007.
J. H. C. Reiber, M. Adame, P. J. H. de Koning, R. van 't Klooster, I. Isgum, K. DeMarco and R. J. van der Geest, "Magnetic resonance angiography and vessel wall imaging: great tools for assessing atherosclerosis", North American Society for Cardiovascular Imaging}, 2007.
phd theses
20TOTAL RESOURCES
J. Sander, "Assessing anatomy and function of the heart using 4D cardiac MRI and deep learning", University of Amsterdam, The Netherlands, 2023, ISBN: 978-94-6419-911-6.R. Zoetmulder, "Deep-learning-based image segmentation for uncommon ischemic stroke: from infants to adults", University of Amsterdam, The Netherlands, 2023.
S. Bruns, "Automated segmentation of the heart in high-dimensional computed tomography", University of Amsterdam, The Netherlands, 2022, ISBN: 978-94-6419-536-1.
S.G.M. van Velzen, "AI-based Analysis of Cardiovascular Disease Risk in CT of Breast Cancer Patients", Utrecht University, The Netherlands, 2021, ISBN: 978-94-6419-173-8.
M. Zreik, "Machine learning for coronary artery disease analysis in cardiac CT", Utrecht University, The Netherlands, 2020, ISBN: 978-94-6323-978-3.
N. Khalili, "Machine learning for automatic segmentation of neonatal and fetal MR brain images", Utrecht University, The Netherlands, 2020, ISBN: 978-90-393-7324-8.
F. Venhuizen, "Machine Learning for Quantification of Age-Related Macular Degeneration Imaging Biomarkers in Optical Coherence Tomography", 2019.
R. Philipsen, "Automated chest radiography reading. Improvements, validation, and cost-effectiveness analysis", 2019.
N. Lessmann, "Machine learning based quantification of extrapulmonary diseases in chest CT", Utrecht University, The Netherlands, 2019, ISBN: 978-94-6323-607-2..
R. W. van Hamersvelt, "New dimensions in cardiovascular CT", Utrecht University, The Netherlands, 2019, ISBN: 978-90-393-7092-6.
J. Šprem, "Enhanced cardiovascular risk prediction by machine learning", Utrecht University, The Netherlands, 2019, ISBN: 978-94-6323-713-0.
B. D. de Vos, "Machine learning for cardiovascular disease analysis in chest CT", Utrecht University, The Netherlands, 2018, ISBN: 978-90-393-7065-0..
J. M. Wolterink, "Machine learning based analysis of cardiovascular images", Utrecht University, The Netherlands, 2017, ISBN: 978-94-6299-587-1.
M. van Grinsven, "Automated analysis of retinal images for detection of age-related macular degeneration and diabetic retinopathy", 2016.
P. Moeskops, "Automatic MRI-based quantification of brain characteristics in preterm newborns", Utrecht University, The Netherlands, 2016, ISBN: 978-90-393-6625-7.
P. Maduskar, "Automated analysis of tuberculosis in chest radiographs", 2015.
J. Melendez, "Improving computer-aided detection systems through advanced pattern recognition techniques", 2015.
L. E. Hogeweg, "Automatic detection of tuberculosis in chest radiographs", 2013.
C. I. Sánchez, "Retinal image analysis by mixture model based clustering and discriminant analysis for automatic detection of hard exudates and haemorhages: A tool for diabetic retinopathy screening", 2008.
I. Isgum, "Computer-aided detection and quantification of arterial calcifications with CT", Utrecht University, The Netherlands, 2007, ISBN: 978-90-393-4528-3.
master theses
2TOTAL RESOURCES
W. Lodewijk, "Automatic fetal brain segmentation using convolutional neural networks", 2022.T. Snelleman, "Coronary Artery Extraction using Geometrical Deep Learning on Medical Imaging Data", 2022.
preprint
7TOTAL RESOURCES
A. R. Krishnan, K. Xu, T. Li, C. Gao, L. W. Remedios, P. Kanakaraj, H. H. Lee, S. Bao, K. L. Sandler, F. Maldonado, I. Isgum, B. A Landman, "Inter-vendor harmonization of Computed Tomography (CT) reconstruction kernels using unpaired image translation", arXiv:arXiv:2309.12953, 2023.N. Hampe, S. G. M. van Velzen, J. P. Aben, C. Collet, I. Išgum, "Deep Learning-Based Prediction of Fractional Flow Reserve along the Coronary Artery", arXiv:2308.04923, 2023.
C. de Vente, L. H. Boulogne, K. V. Venkadesh, C. Sital, N. Lessmann, C. Jacobs, C. I. Sánchez and B. van Ginneken, "Improving Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: An Ablation Study", arXiv:200.909.725, 2020.
P. L. Muller, B. Liefers, T. Treis, F. Gomes Rodrigues, A. Olvera-Barrios, B. Paul, N. Dhingra, A. Lotery, C. Bailey, P. Taylor, C. I. Sánchez and A. Tufail, "Reliability of retinal pathology quantification in age-related macular degeneration: Implications for clinical trials and machine learning applications", 2020.
S. C. Wetstein, C. González-Gonzalo, G. Bortsova, B. Liefers, F. Dubost, I. Katramados, L. Hogeweg, B. van Ginneken, J. P. W. Pluim, M. de Bruijne, C. I. Sánchez and M. Veta, "Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors", arXiv:200.606.356, 2020.
B. Liefers, J. M. Colijn, C. González-Gonzalo, T. Verzijden, P. Mitchell, C. B. Hoyng, B. van Ginneken, C. C. Klaver and C. I. Sánchez, "A deep learning model for segmentation of geographic atrophy to study its long-term natural history", arXiv:190.805.621, 2019.
C. González-Gonzalo, B. Liefers, B. van Ginneken and C. I. Sánchez, "Iterative augmentation of visual evidence for weakly-supervised lesion localization in deep interpretability frameworks", arXiv:191.007.373, 2019.
book chapters
6TOTAL RESOURCES
B. D. de Vos, H. Sokooti, M. Staring, I. Isgum, "Machine Learning in Image Registration", pp. 501-515, Elsevier Science Publishing, 2023, ISBN: 9780128136577.S.G.M van Velzen, N. Hampe, B.D. de Vos, I. Isgum, "Artificial intelligence-based evaluation of coronary calcium", pp. 245-257, In: De Cecco, C.N., van Assen, M., Leiner, T. (eds) Artificial intelligence in cardiothoracic imaging. Humana, Cham, 2022, ISBN: 978-3-030-92087-6.
P.J. Slomka, R.J.H. Miller, I. Isgum, D. Dey, "Nuclear Cardiology and Multimodal Cardiovascular Imaging: Artificial Intelligence in Nuclear Cardiology", pp. 451, Elsevier, 2022, ISBN: 9780323763035.
J. Verjans, W. B. Veldhuis, G. Carneiro, J. M. Wolterink, I. Išgum and T. Leiner, "Cardiovascular Diseases", pp. 167-185, In: E.R. Ranschaert, S. Morozov, P.R. Algra (Ed.): Artificial Intelligence in Medical Imaging - Opportunities, Applications and Risks, Springer International Publishing , 2019, ISBN: 978-3-319-94878-2.
T. Leiner, J. M. Wolterink and I. Išgum, "Artificial intelligence and cardiovascular disease – friend or foe?", pp. 148-155, In: J. Bremerich, R. Salgado (Ed.): The heart revealed - Radiology in the diagnosis and management of cardiac conditions , pp. 148-155 , The European Society of Radiology (ESR), 2018, ISBN: 978-3-9504388-5-7.
J. M. Wolterink, K. Kamnitsas, C. Ledig and I. Išgum, "Deep learning: generative adversarial networks and adversarial methods", pp. 547-574, In: Handbook of Medical Image Computing and Computer Assisted Intervention, 2018, ISBN: 978-0-12-816176-0.
others
3TOTAL RESOURCES
I. Isgum, B. A. Landman, T. Vrtovec, "Special Section Guest Editorial: Advances in High-Dimensional Medical Image Processing", Journal of Medical Imaging, 2022.I. Isgum, A. Rutten, M. Prokop and B. van Ginneken, "Automated Calcium Scoring for Risk Assessment of Coronary Artery Disease", 2005.
I. Isgum and B. van Ginneken, "CT segmentation programs extract calcifications", Diagnostic Imaging Europe, 2003.