PROJECT LEADER
Automatic analysis of the developing neonatal brain
Developing AI methods for automatic and quantitative analysis of neonatal brain with MRI.
FINISHED
2012
|
2016
RESEARCH AREAS
About project
Preterm birth is often associated with impaired neurodevelopment. Quantitative evaluation of MR images may indicate the state and expected progression of brain development in preterm born infants and aid in the decision of future interventions. Segmentation of different tissue types in the brain is a prerequisite for obtaining such MRI measurements. In this project, we design methods for automatic and quantitative analysis of neonatal MR brain images in a longitudinally imaged cohort of preterm infants, focusing on brain tissue volumes and cortical morphology. This project is a collaboration between the Department of Neonatology and Image Sciences Institute at the UMC Utrecht.
Members
Our publications & software
Publications
Journal articlesP. 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.
InproceedingsN. 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.
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).
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.
PHD thesesP. Moeskops, "Automatic MRI-based quantification of brain characteristics in preterm newborns", Utrecht University, The Netherlands, 2016, ISBN: 978-90-393-6625-7.
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. 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.
AbstractsP. 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.
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.
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.
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.
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.
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.
Software