Artificial Intelligence in Diffusion MRI: Enhanced Cuckoo Search Algorithm with Metaheuristic Components for Extracting the Maxima of the Orientation Distribution Function

Description

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. Front Matter ....Pages i-xvii Introduction of Diffusion MRI and Cuckoo Search Algorithm (Mohammad Shehab)....Pages 1-12 Background of Diffusion MRI (Mohammad Shehab)....Pages 13-30 Cuckoo Search Algorithm (Mohammad Shehab)....Pages 31-59 Methodology of Extracting the ODF Maxima Using CSA (Mohammad Shehab)....Pages 61-76 Adaptive Cuckoo Search Algorithm for Extracting the ODF Maxima (Mohammad Shehab)....Pages 77-89 Modified Cuckoo Search Algorithm (MCSA) For Extracting the ODF Maxima (Mohammad Shehab)....Pages 91-110 Hybridization Cuckoo Search Algorithm for Extracting the ODF Maxima (Mohammad Shehab)....Pages 111-146 Apply CSAHC-ODF Algorithm for Extracting the ODF Maxima from the Human Brain’s Data (Mohammad Shehab)....Pages 147-153 Conclusion and Future Work (Mohammad Shehab)....Pages 155-157