LEADER 05423nam 22008415 450 001 996466073303316 005 20200704100044.0 010 $a3-319-27929-7 024 7 $a10.1007/978-3-319-27929-9 035 $a(CKB)4340000000001258 035 $a(SSID)ssj0001599550 035 $a(PQKBManifestationID)16306003 035 $a(PQKBTitleCode)TC0001599550 035 $a(PQKBWorkID)14892307 035 $a(PQKB)11154099 035 $a(DE-He213)978-3-319-27929-9 035 $a(MiAaPQ)EBC6307361 035 $a(MiAaPQ)EBC5578561 035 $a(Au-PeEL)EBL5578561 035 $a(OCoLC)1066191993 035 $a(PPN)19088486X 035 $a(EXLCZ)994340000000001258 100 $a20151229d2015 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aMachine Learning Meets Medical Imaging$b[electronic resource] $eFirst International Workshop, MLMMI 2015, Held in Conjunction with ICML 2015, Lille, France, July 11, 2015, Revised Selected Papers /$fedited by Kanwal Bhatia, Herve Lombaert 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (X, 105 p. 31 illus. in color.) 225 1 $aImage Processing, Computer Vision, Pattern Recognition, and Graphics ;$v9487 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-319-27928-9 320 $aIncludes bibliographical references and index. 327 $aRetrospective motion correction of magnitude-input MR images -- Automatic Brain Localization in Fetal MRI Using Superpixel Graphs -- Learning Deep Temporal Representations for fMRI Brain Decoding -- Modelling Non-Stationary and Non-Separable Spatio-Temporal Changes in Neurodegeneration via Gaussian Process Convolution -- Improving MRI brain image classification with anatomical regional kernels -- A Graph Based Classification Method for Multiple Sclerosis Clinical Form Using Support Vector Machine -- Classification of Alzheimer?s Disease using Discriminant Manifolds of Hippocampus Shapes -- Transfer Learning for Prostate Cancer Mapping Based on Multicentric MR imaging databases. 330 $aNormal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} This book constitutes the revised selected papers of the First International Workshop on Machine Learning in Medical Imaging, MLMMI 2015, held in July 2015 in Lille, France, in conjunction with the 32nd International Conference on Machine Learning, ICML 2015. The 10 papers presented in this volume were carefully reviewed and selected for inclusion in the book. The papers communicate the specific needs and nuances of medical imaging to the machine learning community while exposing the medical imaging community to current trends in machine learning. . 410 0$aImage Processing, Computer Vision, Pattern Recognition, and Graphics ;$v9487 606 $aOptical data processing 606 $aArtificial intelligence 606 $aBioinformatics 606 $aPattern recognition 606 $aAlgorithms 606 $aComputers 606 $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aComputational Biology/Bioinformatics$3https://scigraph.springernature.com/ontologies/product-market-codes/I23050 606 $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X 606 $aAlgorithm Analysis and Problem Complexity$3https://scigraph.springernature.com/ontologies/product-market-codes/I16021 606 $aComputation by Abstract Devices$3https://scigraph.springernature.com/ontologies/product-market-codes/I16013 615 0$aOptical data processing. 615 0$aArtificial intelligence. 615 0$aBioinformatics. 615 0$aPattern recognition. 615 0$aAlgorithms. 615 0$aComputers. 615 14$aImage Processing and Computer Vision. 615 24$aArtificial Intelligence. 615 24$aComputational Biology/Bioinformatics. 615 24$aPattern Recognition. 615 24$aAlgorithm Analysis and Problem Complexity. 615 24$aComputation by Abstract Devices. 676 $a006.31 702 $aBhatia$b Kanwal$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aLombaert$b Herve$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466073303316 996 $aMachine Learning Meets Medical Imaging$92597697 997 $aUNISA