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Our PUBLICATIONS
journal articles
7TOTAL RESOURCES
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.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.
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.
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.
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.
inproceedings
1TOTAL RESOURCES
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.abstracts
3TOTAL RESOURCES
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.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.
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.
phd theses
1TOTAL RESOURCES
R. W. van Hamersvelt, "New dimensions in cardiovascular CT", Utrecht University, The Netherlands, 2019, ISBN: 978-90-393-7092-6.