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Diffusion MRI abnormalities detection with orientation distribution functions: A multiple sclerosis longitudinal study
Abstract : We propose a new algorithm for the voxelwise analysis of orientation distribution functions between one image and a group of reference images. It relies on a generic framework for the comparison of diffusion probabilities on the sphere, sampled from the underlying models. We demonstrate that this method, combined to dimensionality reduction through a principal component analysis, allows for more robust detection of lesions on simulated data when compared to classical tensor-based analysis. We then demonstrate the efficiency of this pipeline on the longitudinal comparison of multiple sclerosis patients at an early stage of the disease: right after their first clinically isolated syndrome (CIS) and three months later. We demonstrate the pre-dictive value of ODF-based scores for the early detection of lesions that will appear or heal.
Cited literature [26 references]
https://www.hal.inserm.fr/inserm-01134107
Contributor : Olivier Commowick <>
Submitted on : Sunday, March 22, 2015 - 5:04:29 PM
Last modification on : Thursday, December 19, 2019 - 1:36:16 AM
Document(s) archivé(s) le : Monday, April 17, 2017 - 8:44:17 PM
Contributor : Olivier Commowick <>
Submitted on : Sunday, March 22, 2015 - 5:04:29 PM
Last modification on : Thursday, December 19, 2019 - 1:36:16 AM
Document(s) archivé(s) le : Monday, April 17, 2017 - 8:44:17 PM
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