000 04457nam a22006255i 4500
001 978-3-319-27929-9
003 DE-He213
005 20240730195619.0
007 cr nn 008mamaa
008 151229s2015 sz | s |||| 0|eng d
020 _a9783319279299
_9978-3-319-27929-9
024 7 _a10.1007/978-3-319-27929-9
_2doi
050 4 _aTA1634
072 7 _aUYQV
_2bicssc
072 7 _aCOM016000
_2bisacsh
072 7 _aUYQV
_2thema
082 0 4 _a006.37
_223
245 1 0 _aMachine Learning Meets Medical Imaging
_h[electronic resource] :
_bFirst International Workshop, MLMMI 2015, Held in Conjunction with ICML 2015, Lille, France, July 11, 2015, Revised Selected Papers /
_cedited by Kanwal Bhatia, Herve Lombaert.
250 _a1st ed. 2015.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aX, 105 p. 31 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
_x3004-9954 ;
_v9487
505 0 _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.
520 _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. .
650 0 _aComputer vision.
_9160850
650 0 _aArtificial intelligence.
_93407
650 0 _aBioinformatics.
_99561
650 0 _aPattern recognition systems.
_93953
650 0 _aAlgorithms.
_93390
650 0 _aComputer science.
_99832
650 1 4 _aComputer Vision.
_9160851
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aComputational and Systems Biology.
_931619
650 2 4 _aAutomated Pattern Recognition.
_931568
650 2 4 _aAlgorithms.
_93390
650 2 4 _aTheory of Computation.
_9160852
700 1 _aBhatia, Kanwal.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9160853
700 1 _aLombaert, Herve.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9160854
710 2 _aSpringerLink (Online service)
_9160855
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319279282
776 0 8 _iPrinted edition:
_z9783319279305
830 0 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
_x3004-9954 ;
_v9487
_9160856
856 4 0 _uhttps://doi.org/10.1007/978-3-319-27929-9
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
942 _cELN
999 _c95709
_d95709