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Inferring Cerebral White Matter Fibres from Diffusion Tensor Magnetic Resonance Images

Hu, Chengliang (2018) Inferring Cerebral White Matter Fibres from Diffusion Tensor Magnetic Resonance Images. PhD thesis, University of York.

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Thesis_ChengliangHu_25Oct2018.pdf - Examined Thesis (PDF)
Restricted until 25 April 2020.

Abstract

The dissertation describes the research work on the inference of cerebral white matter fibres from diffusion tensor magnetic resonance images (DT-MRI), derived from the high angular resolution diffusion-weighted imaging (HARDI) data. A novel framework for inferring cerebral white matter fibres from diffusion MR images is presented. It includes feature extraction using graph based methods; feature selection with statistical pattern recognition techniques; and the inference of the white matter fibres applying machine learning methods. Four similarity measures are adopted or proposed for the fibre characterisation. Very good results are produced and a comparison is made. An evaluation of the methodology is conducted on real diffusion MRI data.

Item Type: Thesis (PhD)
Keywords: Diffusion Tensor MRI, DT-MRI, DTI, HARDI, graph theory, white matter fibres, sulci, classification.
Academic Units: The University of York > Computer Science (York)
Depositing User: Dr Chengliang Hu
Date Deposited: 03 Dec 2018 16:24
Last Modified: 03 Dec 2018 16:24
URI: http://etheses.whiterose.ac.uk/id/eprint/22002

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