journal articles

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.
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.
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..
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.
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).
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.
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.
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.


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.
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.
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.


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.
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.

phd theses

P. Moeskops, "Automatic MRI-based quantification of brain characteristics in preterm newborns", Utrecht University, The Netherlands, 2016, ISBN: 978-90-393-6625-7.