CERES: A new cerebellum lobule segmentation method.

TitleCERES: A new cerebellum lobule segmentation method.
Publication TypeJournal Article
Year of Publication2017
AuthorsRomero JE, Coupé P, Giraud R, Ta V-T, Fonov V, Park MTae M, M Chakravarty M, Voineskos AN, Manjón JV
JournalNeuroimage
Volume147
Pagination916-924
Date Published2017 Feb 15
ISSN1095-9572
Abstract

The human cerebellum is involved in language, motor tasks and cognitive processes such as attention or emotional processing. Therefore, an automatic and accurate segmentation method is highly desirable to measure and understand the cerebellum role in normal and pathological brain development. In this work, we propose a patch-based multi-atlas segmentation tool called CERES (CEREbellum Segmentation) that is able to automatically parcellate the cerebellum lobules. The proposed method works with standard resolution magnetic resonance T1-weighted images and uses the Optimized PatchMatch algorithm to speed up the patch matching process. The proposed method was compared with related recent state-of-the-art methods showing competitive results in both accuracy (average DICE of 0.7729) and execution time (around 5 minutes).

DOI10.1016/j.neuroimage.2016.11.003
Alternate JournalNeuroimage
PubMed ID27833012

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