Quantitative analysis of nutrition supplements on neonatal brain development

In extremely preterm infants, brain growth is disrupted and an essential part of its development takes place ex utero. Consequently, over 50% of these infants exhibit cognitive disabilities and behavioral problems. In this project, the effect of nutrition supplements on brain development in preterm infants will be evaluated. Using techniques from the field of medical image analysis and machine learning, MR images allow computation of quantitative descriptors measuring brain tissue volumes and cortical folding that may provide information about brain development in extremely preterm infants using MR imaging at term-equivalent age.

Researchers


Journal Articles

1.

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, I. Išgum

Automatic extraction of the intracranial volume in fetal and neonatal MR scans using convolutional neural networks Journal Article

NeuroImage Clinical, 24 (102061), 2019.

Abstract | Links | BibTeX

2.

N. Khalili, N. Lessmann, E. Turk, N. Claessens, R. de Heus, T. Kolk, M.A. Viergever, M.J.N.L. Benders, I. Išgum

Automatic brain tissue segmentation in fetal MRI using convolutional neural networks Journal Article

Magnetic Resonance Imaging, 64 , pp. 77-89, 2019.

Abstract | Links | BibTeX

Inproceedings

1.

N. Khalili, E. Turk, M. Zreik, M.A. Viergever, M.J.N.L. Benders, I. Išgum

Generative adversarial network for segmentation of motion affected neonatal brain MRI Inproceedings

In: Medical Image Computing and Computer Assisted Intervention (MICCAI 2019), Lecture Notes in Computer Science, 2019.

Links | BibTeX

2.

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, I. Išgum

Automatic segmentation of the intracranial volume in fetal MR images Inproceedings

In: MICCAI Workshop on Fetal and InFant Image analysis (FIFI 2017), 2017.

Abstract | Links | BibTeX

Abstracts

1.

N. Khalili, N. Lessmann, E. Turk, M.A. Viergever, M.J.N.L. Benders, I. Išgum

Brain tissue segmentation in fetal MRI using convolutional neural networks with simulated intensity inhomogeneities Abstract

In: International Society for Magnetic Resonance in Medicine, 27th Annual Meeting & Exhibition, 2019.

Abstract | BibTeX