- -

NABS: non-local automatic brain hemisphere segmentation

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by


NABS: non-local automatic brain hemisphere segmentation

Show full item record

Romero Gomez, JE.; Manjón Herrera, JV.; Tohka, J.; Coupé, P.; Robles Viejo, M. (2015). NABS: non-local automatic brain hemisphere segmentation. Magnetic Resonance Imaging. 33(4):474-484. doi:10.1016/j.mri.2015.02.005

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/65655

Files in this item

Item Metadata

Title: NABS: non-local automatic brain hemisphere segmentation
UPV Unit: Universitat Politècnica de València. Instituto Universitario de Aplicaciones de las Tecnologías de la Información - Institut Universitari d'Aplicacions de les Tecnologies de la Informació
Universitat Politècnica de València. Departamento de Física Aplicada - Departament de Física Aplicada
Issued date:
In this paper, we propose an automatic method to segment the five main brain sub-regions (i.e. left/right hemispheres, left/right cerebellum and brainstem) from magnetic resonance images. The proposed method uses a library ...[+]
Subjects: Asymmetry , Brain segmentation , Brain volume analysis , MRI , Patch-based segmentation
Copyrigths: Reserva de todos los derechos
Magnetic Resonance Imaging. (issn: 0730-725X )
DOI: 10.1016/j.mri.2015.02.005
Publisher version: http://dx.doi.org/10.1016/j.mri.2015.02.005
Project ID: info:eu-repo/grantAgreement/NIH/NATIONAL CENTER FOR RESEARCH RESOURCES/5U24RR021382-04/US
Description: "NOTICE: this is the author’s version of a work that was accepted for publication in Magnetic Resonance Imaging. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Magnetic Resonance Imaging, [Volume 33, Issue 4, May 2015, Pages 474–484] DOI 10.1016/j.mri.2015.02.005
We want to thank the OASIS (P50 AG05681, P01 AG03991, R01 AG021910, P50 MH071616, U24 RR021382, R01 MH56584) and IXI - Information eXtraction from Images (EPSRC GR/S21533/02) datasets promoters for making available this ...[+]
Type: Artículo

This item appears in the following Collection(s)

Show full item record