Automatic analysis of the developing neonatal brain

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.


Segmentation_30wksCroppedSegmentation_40wksCropped
Automatic segmentation of images acquired at 30 (left) and 40 weeks postmenstrual age (right), in unmyelinated white matter (red), cortical grey matter (yellow), and cerebrospinal fluid in the extracerebral space (blue).


Researchers


Journal Articles

1.

P. Moeskops, J. de Bresser, H.J Kuijf, A.M Mendrik, G.J. Biessels, J.P. Pluim, I. Išgum

Evaluation of a deep learning approach for the segmentation of brain tissues and white matter hyperintensities of presumed vascular origin in MRI Journal Article

NeuroImage Clinical, 17 , pp. 251-262, 2017.

Abstract | Links | BibTeX

2.

P. Moeskops, I. Isgum, K. Keunen, N.H.P. Claessens, I.C. van Haastert, F. Groenendaal, L.S. de Vries, M.A. Viergever, M.J.N.L. Benders

Prediction of cognitive and motor outcome of preterm infants based on automatic quantitative descriptors from neonatal MR brain images Journal Article

Scientific Reports, 7 (2163), 2017.

Abstract | Links | BibTeX

3.

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.-F. Mangin, M.A. Viergever, J. Dubois, M.J.N.L. Benders

Relation between clinical risk factors, early cortical changes, and neurodevelopmental outcome in preterm infants Journal Article

NeuroImage, 5 (142), pp. 301-310, 2016.

BibTeX

4.

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, M. von Rhein

Delayed cortical gray matter development in neonates with severe congenital heart disease Journal Article

Pediatric Research, 80 (5), pp. 668-674, 2016.

BibTeX

5.

P. Moeskops, M.A. Viergever, A.M. Mendrik, L.S. de Vries, M.J.N.L. Benders, I. Isgum

Automatic segmentation of MR brain images with a convolutional neural network Journal Article

IEEE Transactions on Medical Imaging, 35 (5), pp. 1252-1261, 2016.

Abstract | BibTeX

6.

P. Moeskops; M.J.N.L. Benders; K.J. Kersbergen; F. Groenendaal; L.S. de Vries; M.A. Viergever; I. Išgum

Development of cortical morphology evaluated with longitudinal MR brain images of preterm infants Journal Article

PLOS ONE, 10 (7), pp. e0131552, 2015.

Abstract | BibTeX

7.

P. Moeskops, M.J.N.L. Benders, S.M. Chita, K.J. Kersbergen, F. Groenendaal, L.S. de Vries, M.A. Viergever, I. Išgum

Automatic segmentation of MR brain images of preterm infants using supervised classification Journal Article

NeuroImage, 118 , pp. 628-641, 2015.

Abstract | BibTeX

8.

I. Isgum, M.J.N.L. Benders, B. Avants, M.J. Cardoso, S.J. Counsell, E. Fischi 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, M.A. Viergever

Evaluation of automatic neonatal brain segmentation algorithms: the NeoBrainS12 challenge Journal Article

Medical Image Analysis, 20 (1), pp. 135-151, 2015.

Abstract | BibTeX

Inproceedings

1.

P. Moeskops, J.M. Wolterink, B.H.M. van der Velden, K.G.A. Gilhuijs, T. Leiner, M.A. Viergever, I. Isgum

Deep learning for multi-task medical image segmentation in multiple modalities Inproceedings

In: Medical Image Computing and Computer-Assisted Intervention, pp. 478-486, 2016.

Abstract | BibTeX

2.

P. Moeskops; M.A. Viergever; M.J.N.L. Benders; I. Isgum

Evaluation of an automatic brain segmentation method developed for neonates on adult MR brain images Inproceedings

In: SPIE Medical Imaging, pp. 941315, 2015.

Abstract | BibTeX

3.

P. Moeskops; M.J.N.L. Benders; P.C. Pearlman; K.J. Kersbergen; A. Leemans; M.A. Viergever; I. Isgum

Assessment of quantitative cortical biomarkers in the developing brain of preterm infants Inproceedings

In: SPIE Medical Imaging, pp. 867011, 2013.

Abstract | BibTeX

4.

S.M. Chita; M.J.N.L. Benders; P. Moeskops; K.J. Kersbergen; M.A. Viergever; I. Isgum

Automatic segmentation of the preterm neonatal brain with MRI using supervised classification Inproceedings

In: SPIE Medical Imaging, pp. 86693X-1-86693X-6, 2013.

Abstract | BibTeX

Abstracts

1.

P. Moeskops, N.C. A'Campo, M.J.N.L. Benders, L.S. de Vries, M.A. Viergever, I. Isgum

Automatic whole brain segmentation of MR brain images of preterm infants and adults using supervised classification Abstract

In: 2015.

BibTeX

2.

P. Moeskops; M.J.N.L. Benders; A. Buchmann; B. Latal; W. Knirsch; L.S. de Vries; C. Hagmann; I. Isgum; M. Von Rhein

Cortical morphology in infants with congenital heart disease pre- and post-surgery Abstract

In: 2014.

Abstract | BibTeX

3.

P. Moeskops; I. Isgum; K.J. Kersbergen; F. Groenendaal; L.S. de Vries; M.A. Viergever; M.J.N.L. Benders

Quantitative evaluation of cortical development in serial MR images of preterm infants Abstract

In: 2013.

Abstract | BibTeX