LEADER 03538nam 22006973 450 001 9910548277003321 005 20230725152821.0 010 $a3-030-95136-7 035 $a(CKB)5590000000896792 035 $a(MiAaPQ)EBC6897088 035 $a(Au-PeEL)EBL6897088 035 $a(OCoLC)1308501391 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/79362 035 $a(PPN)260828440 035 $a(EXLCZ)995590000000896792 100 $a20220321d2022 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMathematical Modeling of the Human Brain $eFrom Magnetic Resonance Images to Finite Element Simulation / Kent-Andre? Mardal, Marie E. Rognes, Travis B. Thompson, Lars Magnus Valnes 205 $a1st edition. 210 $aCham$cSpringer Nature$d2022 210 1$aCham :$cSpringer International Publishing AG,$d2022. 210 4$dŠ2022. 215 $a1 online resource (129 pages) $c(XVI, 118 p. 32 illus., 25 illus. in color. :) 225 1 $aSimula SpringerBriefs on Computing ;$vv.10 311 0 $a3-030-95135-9 327 $aIntroduction --Working with magnetic resonance images of the brain --From T1 images to numerical simulation --Introducing heterogeneities --Introducing directionality with diffusion tensors --Simulating anisotropic diffusion in heterogeneous brain regions --Concluding remarks and outlook --References --Index. 330 $aThis open access book bridges common tools in medical imaging and neuroscience with the numerical solution of brain modelling PDEs. The connection between these areas is established through the use of two existing tools, FreeSurfer and FEniCS, and one novel tool, the SVM-Tk, developed for this book. The reader will learn the basics of magnetic resonance imaging and quickly proceed to generating their first FEniCS brain meshes from T1-weighted images. The book's presentation concludes with the reader solving a simplified PDE model of gadobutrol diffusion in the brain that incorporates diffusion tensor images, of various resolution, and complex, multi-domain, variable-resolution FEniCS meshes with detailed markings of anatomical brain regions. After completing this book, the reader will have a solid foundation for performing patient-specific finite element simulations of biomechanical models of the human brain. 410 0$aSimula SpringerBriefs on Computing :$v10. 606 $aHuman physiology 606 $aBiomathematics 606 $aMathematical models 606 $aCervell$2thub 606 $aImatges per ressonāncia magnčtica$2thub 606 $aModels matemātics$2thub 608 $aLlibres electrōnics$2thub 610 $amagnetic resonance imaging 610 $aMesh generation 610 $amathematical modeling 610 $afinite element methods 610 $ascientific computing 615 0$aHuman physiology. 615 0$aBiomathematics. 615 0$aMathematical models. 615 7$aCervell 615 7$aImatges per ressonāncia magnčtica 615 7$aModels matemātics 700 $aMardal$b Kent-André$0781355 701 $aRognes$b Marie E$01214682 701 $aThompson$b Travis B$096200 701 $aValnes$b Lars Magnus$01214683 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910548277003321 996 $aMathematical Modeling of the Human Brain$92804638 997 $aUNINA