Publication
Title
Super-resolution for multislice diffusion tensor imaging
Author
Abstract
Diffusion weighted magnetic resonance images are often acquired with single shot multislice imaging sequences, because of their short scanning times and robustness to motion. To minimize noise and acquisition time, images are generally acquired with either anisotropic or isotropic low resolution voxels, which impedes subsequent posterior image processing and visualization. In this article, we propose a super-resolution method for diffusion weighted imaging that combines anisotropic multislice images to enhance the spatial resolution of diffusion tensor data. Each diffusion weighted image is reconstructed from a set of arbitrarily oriented images with a low through-plane resolution. The quality of the reconstructed diffusion weighted images was evaluated by diffusion tensor metrics and tractography. Experiments with simulated data, a hardware DTI phantom, as well as in vivo human brain data were conducted. Our results show a significant increase in spatial resolution of the diffusion tensor data while preserving high signal to noise ratio.
Language
English
Source (journal)
Magnetic resonance imaging. - New York
Publication
New York : 2013
ISSN
0730-725X
DOI
10.1002/MRM.24233
Volume/pages
69 :1 (2013) , p. 103-113
ISI
000312725500012
Full text (Publisher's DOI)
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Research group
Project info
Quantitative tomographic segmentation of magnetic resonance images
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identifier
Creation 10.04.2012
Last edited 09.10.2023
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