LEADER 04381nam 22007335 450 001 9910633928503321 005 20251113191944.0 010 $a9783031212062 010 $a3031212061 024 7 $a10.1007/978-3-031-21206-2 035 $a(MiAaPQ)EBC7150693 035 $a(Au-PeEL)EBL7150693 035 $a(CKB)25510547100041 035 $a(OCoLC)1352969860 035 $a(PPN)266348688 035 $a(DE-He213)978-3-031-21206-2 035 $a(EXLCZ)9925510547100041 100 $a20221124d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputational Diffusion MRI $e13th International Workshop, CDMRI 2022, Held in Conjunction with MICCAI 2022, Singapore, Singapore, September 22, 2022, Proceedings /$fedited by Suheyla Cetin-Karayumak, Daan Christiaens, Matteo Figini, Pamela Guevara, Tomasz Pieciak, Elizabeth Powell, Francois Rheault 205 $a1st ed. 2022. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2022. 215 $a1 online resource (156 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v13722 311 08$aPrint version: Cetin-Karayumak, Suheyla Computational Diffusion MRI Cham : Springer,c2022 9783031212055 320 $aIncludes bibliographical references and index. 327 $aData preprocessing -- Slice estimation in diffusion MRI of neonatal and fetal brains in image and spherical harmonics domains using autoencoders -- Super-resolution of manifold-valued diffusion MRI refined by multi-modal imaging -- Lossy compression of multidimensional medical images using sinusoidal activation networks: an evaluation study -- Correction of susceptibility distortion in EPI: a semi-supervised approach with deep learning -- The impact of susceptibility distortion correction protocols on adolescent diffusion MRI measures -- Signal representations -- Diffusion MRI Fibre Orientation Distribution Inpainting -- Fitting a Directional Microstructure Model to Diffusion-Relaxation MRI Data with Self-Supervised Machine Learning -- Stepwise Stochastic Dictionary Adaptation Improves Microstructure Reconstruction with Orientation Distribution Function Fingerprinting -- How can spherical CNNs benefit ML-based diffusion MRI parameter estimation? -- Tractography and WM pathways -- DC2U-Net: Tract Segmentation in Brain White Matter Using Dense Criss-Cross U-Net -- Clustering in Tractography using Autoencoders (CINTA) -- Tractometric Coherence of Fiber Bundles in DTI. 330 $aThis book constitutes the proceedings of the International Workshop on Computational Diffusion MRI, CDMRI 2022, which was held 22 September 2022, in conjunction with MICCAI 2022. The 12 full papers included were carefully reviewed and selected for inclusion in the book. The papers were organized in topical sections as follows: Data processing, Signal representations, Tractography and WM pathways. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v13722 606 $aImage processing$xDigital techniques 606 $aComputer vision 606 $aArtificial intelligence 606 $aEducation$xData processing 606 $aSocial sciences$xData processing 606 $aComputer science$xMathematics 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aArtificial Intelligence 606 $aComputers and Education 606 $aComputer Application in Social and Behavioral Sciences 606 $aMathematics of Computing 615 0$aImage processing$xDigital techniques. 615 0$aComputer vision. 615 0$aArtificial intelligence. 615 0$aEducation$xData processing. 615 0$aSocial sciences$xData processing. 615 0$aComputer science$xMathematics. 615 14$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aArtificial Intelligence. 615 24$aComputers and Education. 615 24$aComputer Application in Social and Behavioral Sciences. 615 24$aMathematics of Computing. 676 $a616.07548 702 $aCetin-Karayumak$b Suheyla 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910633928503321 996 $aComputational diffusion MRI$91409948 997 $aUNINA