Inferring Cerebral White Matter Fibres from Diffusion Tensor Magnetic Resonance Images

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.