LEADER 03275nam 22005655 450 001 9910484013903321 005 20200630150330.0 010 $a3-030-36083-0 024 7 $a10.1007/978-3-030-36083-2 035 $a(CKB)4100000009844705 035 $a(MiAaPQ)EBC6112821 035 $a(DE-He213)978-3-030-36083-2 035 $a(PPN)243769628 035 $a(EXLCZ)994100000009844705 100 $a20191120d2020 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial Intelligence in Diffusion MRI $eEnhanced Cuckoo Search Algorithm with Metaheuristic Components for Extracting the Maxima of the Orientation Distribution Function /$fby Mohammad Shehab 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (170 pages) 225 1 $aStudies in Computational Intelligence,$x1860-949X ;$v877 311 $a3-030-36082-2 327 $aIntroduction Of Diffusion MRI and Cuckoo Search Algorithm -- Background Of Diffusion MRI -- Cuckoo Search Algorithm -- Methodology Of Extracting The Odf Maxima Using Csa. 330 $aThis book focuses on the use of artificial intelligence to address a specific problem in the brain ? the orientation distribution function. It discusses three aspects: (i) Preparing, enhancing and evaluating one of the cuckoo search algorithms (CSA); (ii) Describing the problem: Diffusion-weighted magnetic resonance imaging (DW-MRI) is used for non-invasive investigations of anatomical connectivity in the human brain, while Q-ball imaging (QBI) is a diffusion MRI reconstruction technique based on the orientation distribution function (ODF), which detects the dominant fiber orientations; however, ODF lacks local estimation accuracy along the path. (iii) Evaluating the performance of the CSA versions in solving the ODF problem using synthetic and real-world data. This book appeals to both postgraduates and researchers who are interested in the fields of medicine and computer science. . 410 0$aStudies in Computational Intelligence,$x1860-949X ;$v877 606 $aComputational intelligence 606 $aBiomedical engineering 606 $aArtificial intelligence 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aBiomedical Engineering and Bioengineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T2700X 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 615 0$aComputational intelligence. 615 0$aBiomedical engineering. 615 0$aArtificial intelligence. 615 14$aComputational Intelligence. 615 24$aBiomedical Engineering and Bioengineering. 615 24$aArtificial Intelligence. 676 $a616.07548 700 $aShehab$b Mohammad$4aut$4http://id.loc.gov/vocabulary/relators/aut$0995916 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484013903321 996 $aArtificial Intelligence in Diffusion MRI$92282150 997 $aUNINA