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

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

Author
Mohammad Shehab
Publisher
Springer International Publishing
Language
English
Edition
1st ed. 2020
Year
2020
Page
XVII, 157
ISBN
978-3-030-36082-5,978-3-030-36083-2
File Type
pdf
File Size
6.2 MiB

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.

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