Naslov
Automatic neonatal brain tissue segmentation with MRI

Autori
Srhoj-Egekher, Vedran ; Benders, Manon J. N. L. ; Viergever, Max A. ; Išgum, Ivana

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Progress in Biomedical Optics and Imaging - Proceedings of SPIE / Ourselin, S ; Haynor, DR - : SPIE, 2013

ISBN
978-0-8194-9443-6

Skup
Conference on Medical Imaging 2013: Image Processing

Mjesto i datum
Lake Buena Vista (FL), Sjedinjene Američke Države, 10.02.2013. - 12.02.2013

Vrsta sudjelovanja
Ostalo

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Neonatal brain MRI ; Brain segmentation ; Atlas-based segmentation ; Supervised classification

Sažetak
Volumetric measurements of neonatal brain tissue classes have been suggested as an indicator of long-term neurodevelopmental performance. To obtain these measurements, accurate brain tissue segmentation is needed. We propose a novel method for automatic segmentation of cortical grey matter (CoGM), unmyelinated white matter (UWM), myelinated white matter (MWM), basal ganglia and thalami, brainstem, cerebellum, ventricles, and cerebrospinal fluid in the extracerebral space (CSF) in MRI scans of the brain in preterm infants. For this project, seven preterm born infants, scanned at term equivalent age were used. Axial T1- and T2-weighted scans were acquired with 3T MRI scanner. The automatic segmentation was performed in three subsequent stages where each tissue was labeled. First, a multi-atlas-based segmentation (MAS) was employed to obtain localized, subject specific spatially varying priors for each tissue. Next, based on these priors, two-class classification with k-nearest neighbor (kNN) classifier was performed to obtain the segmentation of each tissue type separately. Last, to refine the final result, and to achieve the segmentation along the tissue boundaries, a multiclass naive Bayes classifier was employed. The results were evaluated against the manually set reference standard and quantified in terms of Dice coefficient (DC) and modified Hausdorff distance (MHD), defined as 95th-percentile of the Hausdorff distance. On average, the method achieved the following DCs: 0.87 for CoGM, 0.91 for UWM, 0.60 for MWM, 0.93 for basal ganglia and thalami, 0.87 for brainstem, 0.94 for cerebellum, 0.86 for ventricles, 0.82 for CSF. The obtained average MHDs were 0.48 mm, 0.44 mm, 3.09 mm, 0.39 mm, 0.62 mm, 0.35 mm, 1.75 mm, 1.13 mm, for each tissue, respectively. The proposed methods achieved high segmentation accuracy for all tissues, except for MWM, and it provides a tool for quantification of brain tissue volumes in axial MRI scans of preterm born infants.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Interdisciplinarne tehničke znanosti

Napomena
Rad je citiran i indexiran u: Web of Science: https://apps.webofknowledge.com/full_record.do? product=UA&search_mode=GeneralSearch&qid=7&SID= E2EWjZ6HlWOd2HxUORi&page=1&doc=3 Scopus: https://www.scopus.com/record/display.uri? eid=2-s2.0- 84878335608&origin=inward&txGid=f4ee2937f0980fd 07bde566c5bd46f27

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