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Artificial Intelligence in Diffusion MRI

Enhanced Cuckoo Search Algorithm with Metaheuristic Components for Extracting the Maxima of the Orientation Distribution Function

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  • © 2020

Overview

Authors:
  1. Mohammad Shehab

    1. Computer Science\Artificial Intelligence Department, Aqaba University of Technology, Aqaba, Jordan

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  • 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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Table of contents (9 chapters)

  1. Front Matter

    Pages i-xvii
    Download chapter PDF

  2. Introduction of Diffusion MRI and Cuckoo Search Algorithm

    • Mohammad Shehab
    Pages 1-12

  3. Background of Diffusion MRI

    • Mohammad Shehab
    Pages 13-30

  4. Cuckoo Search Algorithm

    • Mohammad Shehab
    Pages 31-59

  5. Methodology of Extracting the ODF Maxima Using CSA

    • Mohammad Shehab
    Pages 61-76

  6. Adaptive Cuckoo Search Algorithm for Extracting the ODF Maxima

    • Mohammad Shehab
    Pages 77-89

  7. Modified Cuckoo Search Algorithm (MCSA) For Extracting the ODF Maxima

    • Mohammad Shehab
    Pages 91-110

  8. Hybridization Cuckoo Search Algorithm for Extracting the ODF Maxima

    • Mohammad Shehab
    Pages 111-146

  9. Apply CSAHC-ODF Algorithm for Extracting the ODF Maxima from the Human Brain’s Data

    • Mohammad Shehab
    Pages 147-153

  10. Conclusion and Future Work

    • Mohammad Shehab
    Pages 155-157
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Keywords

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. 

Authors and Affiliations

  • Computer Science\Artificial Intelligence Department, Aqaba University of Technology, Aqaba, Jordan

    Mohammad Shehab

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