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Information-theoretic approach for automated white matter fiber tracts reconstruction

Fiber tracking is the most popular technique for creating white matter connectivity maps from diffusion tensor imaging (DTI). This approach requires a seeding process which is challenging because it is not clear how and where the seeds have to be placed. On the other hand, to enhance the interpretation of fiber maps, segmentation and clustering techniques are applied to organize fibers into anatomical structures. In this paper, we propose a new approach to automatically obtain bundles of fibers grouped into anatomical regions. This method applies an information-theoretic split-and-merge algorithm that considers fractional anisotropy and fiber orientation information to automatically segment white matter into volumes of interest (VOIs) of similar FA and eigenvector orientation. For each VOI, a number of planes and seeds is automati- cally placed in order to create the fiber bundles. The proposed approach avoids the need for the user to define seeding or selection regions. The whole process requires less than a minute and minimal user interaction. The agreement between the automated and manual approaches has been measured for 10 tracts in a DTI brain atlas and found to be almost perfect (kappa > 0.8) and substantial (kappa > 0.6). This method has also been evaluated on real DTI data considering 5 tracts. Agreement was substantial (kappa > 0.6) in most of the cases

This work has been supported by TIN2010-21089-C03-01 and 2009 SGR 643 and FIS PS09/00596 of I+D+I 2009-2012

info:eu-repo/grantAgreement/MICINN//TIN2010-21089-C03-01/ES/CONTENIDO DIGITAL PARA JUEGOS SERIOS: CREACION, GESTION, RENDERIZADO E INTERACCION/

Springer Verlag

Director: Ministerio de Ciencia e Innovación (Espanya)
Generalitat de Catalunya. Agència de Gestió d’Ajuts Universitaris i de Recerca
Autor: Prados Carrasco, Ferran
Boada, Imma
Feixas Feixas, Miquel
Prats Galino, Alberto
Blasco Solà, Gerard
Puig Alcántara, Josep
Pedraza, S.
Data: 2012
Resum: Fiber tracking is the most popular technique for creating white matter connectivity maps from diffusion tensor imaging (DTI). This approach requires a seeding process which is challenging because it is not clear how and where the seeds have to be placed. On the other hand, to enhance the interpretation of fiber maps, segmentation and clustering techniques are applied to organize fibers into anatomical structures. In this paper, we propose a new approach to automatically obtain bundles of fibers grouped into anatomical regions. This method applies an information-theoretic split-and-merge algorithm that considers fractional anisotropy and fiber orientation information to automatically segment white matter into volumes of interest (VOIs) of similar FA and eigenvector orientation. For each VOI, a number of planes and seeds is automati- cally placed in order to create the fiber bundles. The proposed approach avoids the need for the user to define seeding or selection regions. The whole process requires less than a minute and minimal user interaction. The agreement between the automated and manual approaches has been measured for 10 tracts in a DTI brain atlas and found to be almost perfect (kappa > 0.8) and substantial (kappa > 0.6). This method has also been evaluated on real DTI data considering 5 tracts. Agreement was substantial (kappa > 0.6) in most of the cases
This work has been supported by TIN2010-21089-C03-01 and 2009 SGR 643 and FIS PS09/00596 of I+D+I 2009-2012
Format: application/pdf
Accés al document: http://hdl.handle.net/10256/11677
Llenguatge: eng
Editor: Springer Verlag
Col·lecció: info:eu-repo/semantics/altIdentifier/doi/10.1007/s12021-012-9148-z
info:eu-repo/semantics/altIdentifier/issn/1539-2791
info:eu-repo/semantics/altIdentifier/eissn/1559-0089
AGAUR/2009-2014/2009 SGR-643
És part de: info:eu-repo/grantAgreement/MICINN//TIN2010-21089-C03-01/ES/CONTENIDO DIGITAL PARA JUEGOS SERIOS: CREACION, GESTION, RENDERIZADO E INTERACCION/
Drets: Tots els drets reservats
Matèria: Imatgeria per ressonància magnètica
Magnetic resonance imaging
Imatges -- Processament -- Tècniques digitals
Image processing -- Digital techniques
Imatgeria mèdica
Imaging systems in medicine
Títol: Information-theoretic approach for automated white matter fiber tracts reconstruction
Tipus: info:eu-repo/semantics/article
Repositori: DUGiDocs

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