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Authors: Theodosios Gkamas 1 ; Félix Renard 2 ; Christian Heinrich 1 and Stéphane Kremer 1

Affiliations: 1 University of Strasbourg - CNRS and Fédération de Médecine Translationnelle de Strasbourg (FMTS), France ; 2 Gipsa-lab, France

ISBN: 978-989-758-077-2

Keyword(s): Diffusion-weighted MRI, Fourth Order Tensor, Non Euclidean Metric, Nonlinear Dimension Reduction, Permutation Testing.

Related Ontology Subjects/Areas/Topics: Applications ; Classification ; Embedding and Manifold Learning ; Feature Selection and Extraction ; Medical Imaging ; Pattern Recognition ; Software Engineering ; Theory and Methods

Abstract: In this communication, we propose an original statistical model for diffusion-weighted magnetic resonance imaging, in order to determine new biomarkers. Second order tensor (T2) modeling of Orientation Distribution Functions (ODFs) is popular and has benefited of specific statistical models, incorporating appropriate metrics. Nevertheless, the shortcomings of T2s, for example for the modeling of crossing fibers, are well identified. We consider here fourth order tensor (T4) models for ODFs, thus alleviating the T2 shortcomings. We propose an original metric in the T4 parameter space. This metric is incorporated in a nonlinear dimension reduction procedure. In the resulting reduced space, we represent the probability density of the two populations, normal and abnormal, by kernel density estimation with a Gaussian kernel, and propose a permutation test for the comparison of the two populations. Application of the proposed model on synthetic and real data is achieved. The relevance of th e approach is shown. (More)

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Paper citation in several formats:
Gkamas, T.; Renard, F.; Heinrich, C. and Kremer, S. (2015). A Fourth Order Tensor Statistical Model for Diffusion Weighted MRI - Application to Population Comparison.In Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM, ISBN 978-989-758-077-2, pages 277-282. DOI: 10.5220/0005252602770282

@conference{icpram15,
author={Theodosios Gkamas. and Félix Renard. and Christian Heinrich. and Stéphane Kremer.},
title={A Fourth Order Tensor Statistical Model for Diffusion Weighted MRI - Application to Population Comparison},
booktitle={Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,},
year={2015},
pages={277-282},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005252602770282},
isbn={978-989-758-077-2},
}

TY - CONF

JO - Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,
TI - A Fourth Order Tensor Statistical Model for Diffusion Weighted MRI - Application to Population Comparison
SN - 978-989-758-077-2
AU - Gkamas, T.
AU - Renard, F.
AU - Heinrich, C.
AU - Kremer, S.
PY - 2015
SP - 277
EP - 282
DO - 10.5220/0005252602770282

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