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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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Hardback
29 November 2019
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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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    Product Details
    ISBN-13
    9783030360825
    Author
    Mohammad Shehab
    Publisher
    Springer Nature B.V.
    Published
    29 November 2019
    Format
    Hardback

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    RRP: $251.90
    $248.12
    Ships in 3-5 business days

    Delivery estimate

    Hurry up! Current stock:

    Artificial Intelligence in Diffusion MRI

    RRP: $251.90
    $248.12

    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. 

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