A generalized order mixture model for tracing connectivity of white matter fascicles complexity in brain from diffusion MRI

Author:

Puri Ashishi1,Kumar Sanjeev12

Affiliation:

1. Department of Mathematics, Indian Institute of Technology , Roorkee, Roorkee 247667, Uttarakhand, India

2. Mehta Family School of Data Science and Artificial Intelligence , Department of Mathematics, Indian Institute of Technology, Roorkee, Roorkee 247667, Uttarakhand, India

Abstract

Abstract This paper focuses on tracing the connectivity of white matter fascicles in the brain. In particular, a generalized order algorithm based on mixture of non-central Wishart distribution model is proposed for this purpose. The proposed algorithm utilizes the generalization of integer order based approach with the mixture of non-central Wishart distribution model. Pseudo super anomalous behavior of water diffusion inside human brain is the prime motivation of the the present study. We have shown results on multiple synthetic simulations with fibers orientations in two and three directions in each voxel as well as experiments on real data. Synthetic simulations were performed with varying noise levels and diffusion weighting gradient i.e. $b-$values. The proposed model performed outstanding especially for distinguishing closely oriented fibers.

Publisher

Oxford University Press (OUP)

Subject

Applied Mathematics,Pharmacology,General Environmental Science,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation,General Medicine,General Neuroscience

Reference42 articles.

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3. Hyperspherical von Mises–Fisher mixture (HVMF) modelling of high angular resolution diffusion MRI;Bhalerao,2007

4. Magnetic Resonance Imaging

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