Morphology-driven automatic segmentation of MR images of the neonatal brain

Article Article scientifique Article Morphology-driven automatic segmentation of MR images of the neonatal brain eng 2012 author Gui Levy Laura 702098 author Lisowski Radoslaw 641081 author Faundez Tamara 525898 author Hüppi Petra Susan 133591 author Lazeyras François 512748 author Kocher Michel 732193 1565-1579 10.1016/j.media.2012.07.006 22921305 1361-8415 The segmentation of MR images of the neonatal brain is an essential step in the study and evaluation of infant brain development. State-of-the-art methods for adult brain MRI segmentation are not applicable to the neonatal brain, due to large differences in structure and tissue properties between newborn and adult brains. Existing newborn brain MRI segmentation methods either rely on manual interaction or require the use of atlases or templates, which unavoidably introduces a bias of the results towards the population that was used to derive the atlases. We propose a different approach for the segmentation of neonatal brain MRI, based on the infusion of high-level brain morphology knowledge, regarding relative tissue location, connectivity and structure. Our method does not require manual interaction, or the use of an atlas, and the generality of its priors makes it applicable to different neonatal populations, while avoiding atlas-related bias. The proposed algorithm segments the brain both globally (intracranial cavity, cerebellum, brainstem and the two hemispheres) and at tissue level (cortical and subcortical gray matter, myelinated and unmyelinated white matter, and cerebrospinal fluid). We validate our algorithm through visual inspection by medical experts, as well as by quantitative comparisons that demonstrate good agreement with expert manual segmentations. The algorithm's robustness is verified by testing on variable quality images acquired on different machines, and on subjects with variable anatomy (enlarged ventricles, preterm- vs. term-born). Algorithms Brain/anatomy & histology Brain Stem/anatomy & histology Cerebellum/anatomy & histology Humans Infant, Newborn Magnetic Resonance Imaging/methods Dewey 616.0757 Dewey 618 58 Département de pédiatrie, gynécologie et obstétrique 223 62 Département de radiologie et informatique médicale 227 false 284 Groupe Lazeyras Francois (IRM fonctionnelle et métabolique) 539 150 L'imagerie cérébrale 184 Medical image analysis 16 8 e26416d4-f7e6-4e7c-b091-106ba18b59d1 Article (Published version) Private 1-s2.0-S1361841512000989-main.pdf 4623199 application/pdf closedAccess Faculté de médecine / Section de médecine clinique / Département de pédiatrie, gynécologie et obstétrique Faculté de médecine / Section de médecine clinique / Département de radiologie et informatique médicale

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Morphology-driven automatic segmentation of MR images of the neonatal brain	Medical image analysis			2012	897	1

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Lisowski, Radoslaw