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Artificial Intelligence in Diffusion MRI: Enhanced Cuckoo Search Algorithm with Metaheuristic Components for Extracting the Maxima of the Orientation ... (Studies in Computational Intelligence, 877) Hardback - 2019
by Shehab, Mohammad
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- Hardback
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Details
- Title Artificial Intelligence in Diffusion MRI: Enhanced Cuckoo Search Algorithm with Metaheuristic Components for Extracting the Maxima of the Orientation ... (Studies in Computational Intelligence, 877)
- Author Shehab, Mohammad
- Binding Hardback
- Edition 1st ed. 2020
- Condition Used: Good
- Pages 157
- Volumes 1
- Language ENG
- Publisher Springer
- Publication date 2019-11-29
- Illustrated Yes
- Features Illustrated
- Bookseller's Inventory # SONG3030360822
- ISBN 9783030360825 / 3030360822
- Weight 0.94 lbs (0.43 kg)
- Dimensions 9.21 x 6.14 x 0.44 in (23.39 x 15.60 x 1.12 cm)
- Size 6.25x0.50x9.50
- Category Technology & Industrial Arts
- Quantity available 1
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From the rear cover
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.
