ROMERO, Jose; COUPÉ, Pierrick; GIRAUD, Rémi; TA, Vinh-Thong; FONOV, Vladimir; PARK, Min Tae; CHAKRAVARTY, Mallar; VOINESKOS, Aristotle; MANJÓN, Jose

doi:10.1016/j.neuroimage.2016.11.003

Metadatos

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Licencia de uso del documento

http://creativecommons.org/licenses/by-nc-nd/

ROMERO, Jose
ITACA

COUPÉ, Pierrick
Laboratoire Bordelais de Recherche en Informatique [LaBRI]

GIRAUD, Rémi
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Institut Polytechnique de Bordeaux [Bordeaux INP]
Institut de Mathématiques de Bordeaux [IMB]

Idioma

Article de revue

Este ítem está publicado en

NeuroImage. 2016

Elsevier

Resumen en inglés

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).< Leer menos

Palabras clave en inglés

MRI

cerebellum lobule segmentation

non-‐local multi-‐atlas patch-‐based label fusion

optimized patchmatch

URI

https://oskar-bordeaux.fr/handle/20.500.12278/193914

DOI

http://dx.doi.org/10.1016/j.neuroimage.2016.11.003

Proyecto ANR

Translational Research and Advanced Imaging Laboratory - ANR-10-LABX-0057

Orígen

Importado de Hal

Centros de investigación

Institut de Mathématiques de Bordeaux (IMB) - UMR 5251