Overview
- 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)
Part of the book series: Studies in Computational Intelligence (SCI, volume 877)
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About this book
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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Keywords
Table of contents (9 chapters)
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Front Matter
Authors and Affiliations
Bibliographic Information
Book Title: Artificial Intelligence in Diffusion MRI
Book Subtitle: Enhanced Cuckoo Search Algorithm with Metaheuristic Components for Extracting the Maxima of the Orientation Distribution Function
Authors: Mohammad Shehab
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-030-36083-2
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-36082-5Published: 29 November 2019
Softcover ISBN: 978-3-030-36085-6Published: 29 November 2020
eBook ISBN: 978-3-030-36083-2Published: 20 November 2019
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XVII, 157
Number of Illustrations: 7 b/w illustrations, 54 illustrations in colour
Topics: Computational Intelligence, Biomedical Engineering and Bioengineering, Artificial Intelligence