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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.date.accessioned | 2020-10-20T03:31:14Z | |
dc.date.available | 2020-10-20T03:31:14Z | |
dc.date.issued | 2017-12 | es_ES |
dc.identifier.issn | 1053-8119 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/152479 | |
dc.description.abstract | [EN] The importance of the hippocampus in the study of several neurodegenerative diseases such as Alzheimer's disease makes it a structure of great interest in neuroimaging. However, few segmentation methods have been proposed to measure its subfields due to its complex structure and the lack of high resolution magnetic resonance (MR) data. In this work, we present a new pipeline for automatic hippocampus subfield segmentation using two available hippocampus subfield delineation protocols that can work with both high and standard resolution data. The proposed method is based on multi-atlas label fusion technology that benefits from a novel multi-contrast patch match search process (using high resolution T1-weighted and T2-weighted images). The proposed method also includes as post-processing a new neural network-based error correction step to minimize systematic segmentation errors. The method has been evaluated on both high and standard resolution images and compared to other state-of-the-art methods showing better results in terms of accuracy and execution time. | es_ES |
dc.description.sponsorship | This research was supported by Spanish UPV2016-0099 and TIN2013-43457-R grants from UPV and the Ministerio de Economia y Competitividad. 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 Program IdEx Bordeaux (ANR-10-IDEX-03-02, HL-MRI Project), Cluster of excellence CPU and TRAIL (HR-DTI ANR-10-LABX-57) and the CNRS multidisciplinary project "Defi imag'In". We also want to thank Javier Juan Albarracin for his valuable contribution to the development of this method. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | NeuroImage | es_ES |
dc.rights | Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) | es_ES |
dc.subject | In-Vivo MRI | es_ES |
dc.subject | Mild cognitive impairment | es_ES |
dc.subject | Magnetic-Resonance | es_ES |
dc.subject | Label fusion | es_ES |
dc.subject | Computational atlas | es_ES |
dc.subject | Atrophy rates | es_ES |
dc.subject | Images | es_ES |
dc.subject | Protocol | es_ES |
dc.subject | Amygdala | es_ES |
dc.subject | Disease | es_ES |
dc.subject.classification | FISICA APLICADA | es_ES |
dc.title | HIPS: A new hippocampus subfield segmentation method | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.neuroimage.2017.09.049 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/ANR//ANR-10-IDEX-0003/FR/Initiative d’excellence de l’Université de Bordeaux/IDEX BORDEAUX/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/ANR//ANR-10-LABX-0057/FR/Translational Research and Advanced Imaging Laboratory/TRAIL/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/UPV//UPV-2016-0099/ | es_ES |
dc.relation.projectID | 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.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.; Manjón Herrera, JV. (2017). HIPS: A new hippocampus subfield segmentation method. NeuroImage. 163:286-295. https://doi.org/10.1016/j.neuroimage.2017.09.049 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1016/j.neuroimage.2017.09.049 | es_ES |
dc.description.upvformatpinicio | 286 | es_ES |
dc.description.upvformatpfin | 295 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 163 | es_ES |
dc.identifier.pmid | 28958881 | es_ES |
dc.relation.pasarela | S\355208 | es_ES |
dc.contributor.funder | Universitat Politècnica de València | es_ES |
dc.contributor.funder | Ministerio de Economía y Competitividad | es_ES |
dc.contributor.funder | Agence Nationale de la Recherche, Francia | es_ES |
dc.contributor.funder | Centre National de la Recherche Scientifique, Francia | es_ES |