Alessia Biagi
Learning strategies for MRI Surrogates in Brain Imaging and BCI.
Rel. Francesco Paolo Andriulli, Michael, Christian, Merlini Adrien. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2023
Abstract
The purpose of this thesis is to develop an algorithm, which based on some selected parameters, is able to extract from a worldwide database of MRIs, the magnetic resonance closest to the satisfaction of these criteria in other words it can provide a 3D model of a patients’ brain without the specific subject MRI. The first chapter consists of a brief introduction to the anatomy of the brain and the mechanisms of impulse transmission in the network of neurons, then the main neuroimaging techniques are explained, with particular attention to the magnetic resonance that is intended to be avoided with the developed algorithm.
Although this method is very useful, it has numerous limitations, over all waiting times and operation costs
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