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Registration of low-SNR high-resolution diffusion-weighted images

Johnsen, SF; Clark, C; Atkinson, D; (2011) Registration of low-SNR high-resolution diffusion-weighted images. In: (Proceedings) Medical Image Analysis and Understanding MIUA 2011. Green open access

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Abstract

This paper introduces a novel, high-speed scheme for intrasubject registration and segmentation of high-resolution multi-shot diffusion-weighted images. Compared to single-shot sequences, multi-shot have advantages in terms of improved spatial resolution and reduced eddy-current and susceptibility artifacts. However, these sequences have prolonged scan times increasing the risk of subject motion, and, a lower signal to noise ratio (SNR) with smaller voxel volumes. The proposed registration algorithm comprises a hybrid thresholding expectation-maximization segmentation method that can cope with the low-SNR, and registers diffusion-weighted to B0 images through fast detection and matching of features found in edge images derived from floating and reference images. We performed validations of the entire pipeline, including assessment of visual appearance by experts, consistency error computations, and analysis of the segmentation, using volunteer images, and found its performance to be comparable with, or exceeding, that of established solutions.

Type: Proceedings paper
Title: Registration of low-SNR high-resolution diffusion-weighted images
Event: Medical Image Analysis and Understanding MIUA 2011
Location: London
Dates: 2011-07-14 - 2011-07-15
Open access status: An open access version is available from UCL Discovery
Publisher version: http://www.biomedical-image-analysis.co.uk/index.p...
Language: English
Additional information: © 2011. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Department of Imaging
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
URI: https://discovery.ucl.ac.uk/id/eprint/1316407
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