1.

Record Nr.

UNINA9910484013903321

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

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020

ISBN

3-030-36083-0

Edizione

[1st ed. 2020.]

Descrizione fisica

1 online resource (170 pages)

Collana

Studies in Computational Intelligence, , 1860-949X ; ; 877

Disciplina

616.07548

Soggetti

Computational intelligence

Biomedical engineering

Artificial intelligence

Computational Intelligence

Biomedical Engineering and Bioengineering

Artificial Intelligence

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

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. .