Giammarco La Barbera
Robust Segmentation of Corpus Callosum in Multi-Scanner pediatric T1-w MRI using Transfer Learning.
Rel. Filippo Molinari. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2019
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Abstract
The Corpus Callosum (CC) has been intensively studied in adults and it has been shown, for instance, that there is a relationship between its morphology and some neurological diseases. Fewer morphological studies have been conducted on children showing that variations in size and shape might be correlated with Multiple Sclerosis. T1-weighted MR scans are usually employed since the CC is entirely visible and distinguishable in the Mid-Sagittal Plane (MSP). State-of-the-art segmentation algorithms for adults, such as CCSeg and ART-yuki, are difficult to use with pediatric images due to the low contrast-to-noise ratio, short acquisition time (low resolution), presence of other parts of the body.
In this work we present a robust method to segment the Corpus Callosum in Magnetic Resonance Images (MRI) based on Convolutional Neural Networks (CNN) and Transfer Learning
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