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Longitudinal Voxel-based morphometry with unified segmentation: evaluation on simulated Alzheimer’s disease

Ridgway, G.R.; Camara, O.; Scahill, R.I.; Crum, W.R.; Whitcher, B.; Fox, N.C.; Hill, D.L.G.; (2007) Longitudinal Voxel-based morphometry with unified segmentation: evaluation on simulated Alzheimer’s disease. In: Proceedings of Medical Image Understanding and Analysis 2007. (pp. pp. 201-205). British Machine Vision Association: Malvern, UK. Green open access

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Abstract

The goal of this work is to evaluate Voxel-Based Morphometry and three longitudinally-tailored methods of VBM.We use a cohort of simulated images produced by deforming original scans using a Finite Element Method, guided to emulate Alzheimer-like changes. The simulated images provide quite realistic data with a known pattern of spatial atrophy, with which VBM’s findings can be meaningfully compared. We believe this is the first evaluation of VBM for which anatomically-plausible ‘gold-standard’ results are available. The three longitudinal VBM methods have been implemented within the unified segmentation framework of SPM5; one of the techniques is a newly developed procedure, which shows promising potential.

Type: Proceedings paper
Title: Longitudinal Voxel-based morphometry with unified segmentation: evaluation on simulated Alzheimer’s disease
ISBN-13: 9781901725339
Open access status: An open access version is available from UCL Discovery
Publisher version: http://www2.wiau.man.ac.uk/caws/Conferences/43/
Language: English
UCL classification: UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Metabolism and Experi Therapeutics
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Neurodegenerative Diseases
URI: http://discovery.ucl.ac.uk/id/eprint/13845
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