Simulation-based evaluation of susceptibility distortion correction methods in diffusion MRI for connectivity analysis

Détails

ID Serval
serval:BIB_65E37F7A5775
Type
Actes de conférence (partie): contribution originale à la littérature scientifique, publiée à l'occasion de conférences scientifiques, dans un ouvrage de compte-rendu (proceedings), ou dans l'édition spéciale d'un journal reconnu (conference proceedings).
Collection
Publications
Institution
Titre
Simulation-based evaluation of susceptibility distortion correction methods in diffusion MRI for connectivity analysis
Titre de la conférence
IEEE 11th International Symposium on Biomedical Imaging - From Nano to Macro (ISBI)
Auteur⸱e⸱s
Esteban Oscar, Daducci Alessandro, Caruyer Emmanuel, O'Brien Kieran, Carbayo Ledesma Maria J., Bach Cuadra Meritxell, Santos Andres
Adresse
Beijing, April 29 2014-May 2 2014
Statut éditorial
Publié
Date de publication
2014
Peer-reviewed
Oui
Pages
738 - 741
Langue
anglais
Résumé
Connectivity analysis on diffusion MRI data of the whole- brain suffers from distortions caused by the standard echo- planar imaging acquisition strategies. These images show characteristic geometrical deformations and signal destruction that are an important drawback limiting the success of tractography algorithms. Several retrospective correction techniques are readily available. In this work, we use a digital phantom designed for the evaluation of connectivity pipelines. We subject the phantom to a "theoretically correct" and plausible deformation that resembles the artifact under investigation. We correct data back, with three standard methodologies (namely fieldmap-based, reversed encoding-based, and registration- based). Finally, we rank the methods based on their geometrical accuracy, the dropout compensation, and their impact on the resulting connectivity matrices.
Mots-clé
LTS5, Diffusion MRI, Brain connectivity, Distortion correction
Création de la notice
01/07/2014 17:11
Dernière modification de la notice
12/11/2020 7:23
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