Artificial Intelligence in Diffusion MRI

This book focuses on the use of artificial intelligence to address a specific problem in the brain the orientation distribution function. It discusses three aspects: (i) Preparing, enhancing and evaluating one of the cuckoo search algorithms (CSA); (ii) Describing the problem: Diffusion-weighted magnetic resonance imaging (DW-MRI) is used for non-invasive investigations of anatomical connectivity in the human brain, while Q-ball imaging (QBI) is a diffusion MRI reconstruction technique based on the orientation distribution function (ODF), which detects the dominant fiber orientations; however, ODF lacks local estimation accuracy along the path. (iii) Evaluating the performance of the CSA versions in solving the ODF problem using synthetic and real-world data. This book appeals to both postgraduates and researchers who are interested in the fields of medicine and computer science.

Presents a new method of addressing the orientation distribution function (ODF) problem by adapting one of the metaheuristic algorithms, namely the cuckoo search algorithm (CSA) Explains new methods, such as metaheuristic algorithms and components, of addressing a problem in the medical field (i.e., extracting the orientation distribution function) more precisely, in the brain Proposes three improved methods: (i) modified cuckoo search algorithm (MCSA); (ii) hybridizing the MCSA with components of the bat algorithm (CSBA), and (iii) hybridizing the CSBA with hill climbing (CSAHC)

Inhalt
Introduction Of Diffusion MRI and Cuckoo Search Algorithm.- Background Of Diffusion MRI.- Cuckoo Search Algorithm.- Methodology Of Extracting The Odf Maxima Using Csa.<p