Alessandro Di Girolamo
Reproducible segmentation of white matter tractograms using artificial intelligence and spatial fuzzy sets.
Rel. Gabriella Balestra. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2019
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Abstract
Tractography is the only in-vivo technique that allows the extraction of white matter fibers from the brain in a non-invasive way. It is used as a support in neurosurgeries and as research tool to study structural connectivity in both healthy and pathological subjects. It generates, from diffusion Magnetic Resonance (MR) volumes, millions of 3D polylines that are estimates of the path followed by real axons. One important clinical application is the automatic segmentation of precise and anatomically well-defined white matter tracts from whole-brain tractograms, but this task is particularly difficult to accomplish since the large number of streamlines makes the computational costs very high and the anatomical tracts definitions found in literature are usually vague or imprecise.
The purpose of this master thesis is to model, in a reproducible way, the tracts anatomical definitions using fuzzy logic and to extract them from whole-brain tractograms of multiple subjects with the help of clustering techniques
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