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Autore: | Shehab Mohammad |
Titolo: | Artificial Intelligence in Diffusion MRI : Enhanced Cuckoo Search Algorithm with Metaheuristic Components for Extracting the Maxima of the Orientation Distribution Function / / by Mohammad Shehab |
Pubblicazione: | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
Edizione: | 1st ed. 2020. |
Descrizione fisica: | 1 online resource (170 pages) |
Disciplina: | 616.07548 |
Soggetto topico: | Computational intelligence |
Biomedical engineering | |
Artificial intelligence | |
Computational Intelligence | |
Biomedical Engineering and Bioengineering | |
Artificial Intelligence | |
Nota di contenuto: | Introduction Of Diffusion MRI and Cuckoo Search Algorithm -- Background Of Diffusion MRI -- Cuckoo Search Algorithm -- Methodology Of Extracting The Odf Maxima Using Csa. |
Sommario/riassunto: | 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. . |
Titolo autorizzato: | Artificial Intelligence in Diffusion MRI |
ISBN: | 3-030-36083-0 |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910484013903321 |
Lo trovi qui: | Univ. Federico II |
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