This project was developed as per a MSc Thesis and with the intent of reducing the prohibitive acquisition times of Diffusion MRI by leveraging Artificial Inteligence Generative Models in new and non-standard ways. In other words, it focuses on the study of how to use different conditionality degrees in image generation when creating realistic and patient-accurate 3D dMRI scans with on-demand acquisition settings (to be manipulated by clinicians as they see fit). Results discovered show great promise for the application of this technology in the medical field and in the bettering of the patient's quality of life when undergoing such long-winded medical exams.
Version Reasoning: https://docs.google.com/spreadsheets/d/1B5_Ql5ASGs9FEVeXk8zD0ZHQIC3HSqMokjQCglzLffE/edit?usp=sharing
