- -

Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images

Show simple item record

Files in this item

dc.contributor.author Carass, Aaron es_ES
dc.contributor.author Cuzzocreo, Jennifer L. es_ES
dc.contributor.author Han, Shuo es_ES
dc.contributor.author Hernandez-Castillo, Carlos R. es_ES
dc.contributor.author Rasser, Paul E. es_ES
dc.contributor.author Ganz, Melanie es_ES
dc.contributor.author Beliveau, Vincent es_ES
dc.contributor.author Dolz, Jose es_ES
dc.contributor.author Ben Ayed, Ismail es_ES
dc.contributor.author Desrosiers, Christian es_ES
dc.contributor.author Thyreau, Benjamin es_ES
dc.contributor.author Romero Gómez, José Enrique es_ES
dc.contributor.author Coupe, Pierrick es_ES
dc.contributor.author Manjón Herrera, José Vicente es_ES
dc.contributor.author Fonov, Vladimir es_ES
dc.date.accessioned 2020-06-05T03:32:01Z
dc.date.available 2020-06-05T03:32:01Z
dc.date.issued 2018-12 es_ES
dc.identifier.issn 1053-8119 es_ES
dc.identifier.uri http://hdl.handle.net/10251/145394
dc.description.abstract [EN] The human cerebellum plays an essential role in motor control, is involved in cognitive function (i.e., attention, working memory, and language), and helps to regulate emotional responses. Quantitative in-vivo assessment of the cerebellum is important in the study of several neurological diseases including cerebellar ataxia, autism, and schizophrenia. Different structural subdivisions of the cerebellum have been shown to correlate with differing pathologies. To further understand these pathologies, it is helpful to automatically parcellate the cerebellum at the highest fidelity possible. In this paper, we coordinated with colleagues around the world to evaluate automated cerebellum parcellation algorithms on two clinical cohorts showing that the cerebellum can be parcellated to a high accuracy by newer methods. We characterize these various methods at four hierarchical levels: coarse (i.e., whole cerebellum and gross structures), lobe, subdivisions of the vermis, and the lobules. Due to the number of labels, the hierarchy of labels, the number of algorithms, and the two cohorts, we have restricted our analyses to the Dice measure of overlap. Under these conditions, machine learning based methods provide a collection of strategies that are efficient and deliver parcellations of a high standard across both cohorts, surpassing previous work in the area. In conjunction with the rank-sum computation, we identified an overall winning method. es_ES
dc.description.sponsorship The data collection and labeling of the cerebellum was supported in part by the NIH/NINDS grant R01 NS056307 (PI: J.L. Prince) and NIH/NIMH grants R01 MH078160 & R01 MH085328 (PI: S.H. Mostofsky). PMT is supported in part by the NIH/NIBIB grant U54 EB020403. CERES2 development was supported by grant UPV2016-0099 from the Universitat Politecnica de Valencia (PI: J.V. Manjon); the French National Research Agency through the Investments for the future Program IdEx Bordeaux (ANR-10-IDEX-03-02, HL-MRI Project; PI: P. Coupe) and Cluster of excellence CPU and TRAIL (HR-DTI ANR-10-LABX-57; PI: P. Coupe). Support for the development of LiviaNET was provided by the National Science and Engineering Research Council of Canada (NSERC), discovery grant program, and by the ETS Research Chair on Artificial Intelligence in Medical Imaging. The authors wish to acknowledge the invaluable contributions offered by Dr. George Fein (Dept. of Medicine and Psychology, University of Hawaii) in preparing this manuscript. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation ANR/ANR-10-IDEX-03-02 es_ES
dc.relation UPV/UPV2016-0099, es_ES
dc.relation NIH/R01 NS056307 es_ES
dc.relation NIH/R01 MH078160 es_ES
dc.relation NIH/R01 MH085328 es_ES
dc.relation NIH/U54 EB020403 es_ES
dc.relation NINDS/R01 NS056307 es_ES
dc.relation NIMH/R01 MH078160 es_ES
dc.relation NIMH/R01 MH085328 es_ES
dc.relation NIBIB/U54 EB020403 es_ES
dc.relation Université de Bordeaux/ANR-10-IDEX-03-02 es_ES
dc.relation Université de Bordeaux/HR-DTI ANR-10-LABX-57 es_ES
dc.relation.ispartof NeuroImage es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Magnetic resonance imaging es_ES
dc.subject Cerebellar ataxia es_ES
dc.subject Attention deficit hyperactivity disorder es_ES
dc.subject Autism es_ES
dc.subject.classification FISICA APLICADA es_ES
dc.title Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.neuroimage.2018.08.003 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 Carass, A.; Cuzzocreo, JL.; Han, S.; Hernandez-Castillo, CR.; Rasser, PE.; Ganz, M.; Beliveau, V.... (2018). Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images. NeuroImage. 183:150-172. https://doi.org/10.1016/j.neuroimage.2018.08.003 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.neuroimage.2018.08.003 es_ES
dc.description.upvformatpinicio 150 es_ES
dc.description.upvformatpfin 172 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 183 es_ES
dc.identifier.pmid 30099076 es_ES
dc.identifier.pmcid PMC6271471 es_ES
dc.relation.pasarela S\373913 es_ES
dc.contributor.funder Université de Bordeaux es_ES
dc.contributor.funder National Institutes of Health, EEUU es_ES
dc.contributor.funder Universitat Politècnica de València es_ES
dc.contributor.funder Agence Nationale de la Recherche, Francia es_ES
dc.contributor.funder National Institute of Mental Health, EEUU es_ES
dc.contributor.funder Natural Sciences and Engineering Research Council of Canada es_ES
dc.contributor.funder National Institute of Neurological Disorders and Stroke, EEUU es_ES
dc.contributor.funder National Institute of Biomedical Imaging and Bioengineering, EEUU es_ES


This item appears in the following Collection(s)

Show simple item record