- -

CERES: A new cerebellum lobule segmentation method

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

CERES: A new cerebellum lobule segmentation method

Show simple item record

Files in this item

dc.contributor.author Romero Gómez, José Enrique es_ES
dc.contributor.author Coupe, Pierrick es_ES
dc.contributor.author Giraud, Remi es_ES
dc.contributor.author Ta, Vinh-Thong es_ES
dc.contributor.author Fonov, Vladimir es_ES
dc.contributor.author Park, Min Tae M es_ES
dc.contributor.author Chalcravarty, M. Mallar es_ES
dc.contributor.author Voineskos, Aristotle N. es_ES
dc.contributor.author Manjón Herrera, José Vicente es_ES
dc.date.accessioned 2018-05-06T04:15:28Z
dc.date.available 2018-05-06T04:15:28Z
dc.date.issued 2017 es_ES
dc.identifier.issn 1053-8119 es_ES
dc.identifier.uri http://hdl.handle.net/10251/101448
dc.description.abstract [EN] 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). es_ES
dc.description.sponsorship We want to thank the IXI - Information eXtraction from Images (EPSRC GR/S21533/02) datasets promoters for making available a valuable resource to the scientific community. This study has been carried out with financial support from the French State, managed by the French National Research Agency (ANR) in the frame of the Investments for the future Programme IdEx Bordeaux (HL-MRI ANR-10-IDEX-03-02), Cluster of Excellence CPU, TRAIL (HR-DTI ANR-10-LABX-57) and the CNRS multidisciplinary project "Defi Imagln". This research was also supported by the Spanish Grant TIN2013-43457-R from the Ministerio de Economia y competitividad. en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation info:eu-repo/grantAgreement/MINECO//TIN2013-43457-R/ES/CARACTERIZACION DE FIRMAS BIOLOGICAS DE GLIOBLASTOMAS MEDIANTE MODELOS NO-SUPERVISADOS DE PREDICCION ESTRUCTURADA BASADOS EN BIOMARCADORES DE IMAGEN/ es_ES
dc.relation.ispartof NeuroImage es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Cerebellum lobule segmentation es_ES
dc.subject Non-local multi-atlas patch-based label fusion es_ES
dc.subject Optimized PatchMatch es_ES
dc.subject.classification FISICA APLICADA es_ES
dc.title CERES: A new cerebellum lobule segmentation method es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.neuroimage.2016.11.003 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Física Aplicada - Departament de Física Aplicada es_ES
dc.description.bibliographicCitation Romero Gómez, JE.; Coupe, P.; Giraud, R.; Ta, V.; Fonov, V.; Park, MTM.; Chalcravarty, MM.... (2017). CERES: A new cerebellum lobule segmentation method. NeuroImage. 147:916-924. https://doi.org/10.1016/j.neuroimage.2016.11.003 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.neuroimage.2016.11.003 es_ES
dc.description.upvformatpinicio 916 es_ES
dc.description.upvformatpfin 924 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 147 es_ES
dc.relation.pasarela S\327839 es_ES
dc.contributor.funder Ministerio de Economía, Industria y Competitividad es_ES


This item appears in the following Collection(s)

Show simple item record