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020 _a9783030009199
_9978-3-030-00919-9
024 7 _a10.1007/978-3-030-00919-9
_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 in Medical Imaging
_h[electronic resource] :
_b9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings /
_cedited by Yinghuan Shi, Heung-Il Suk, Mingxia Liu.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXII, 409 p. 154 illus., 138 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 ;
_v11046
520 _aThis book constitutes the proceedings of the 9th International Workshop on Machine Learning in Medical Imaging, MLMI 2018, held in conjunction with MICCAI 2018 in Granada, Spain, in September 2018. The 45 papers presented in this volume were carefully reviewed and selected from 82 submissions. They focus on major trends and challenges in the area of machine learning in medical imaging and aim to identify new cutting-edge techniques and their use in medical imaging.
650 0 _aComputer vision.
650 0 _aArtificial intelligence.
650 0 _aMedical informatics.
650 0 _aData mining.
650 1 4 _aComputer Vision.
650 2 4 _aArtificial Intelligence.
650 2 4 _aHealth Informatics.
650 2 4 _aData Mining and Knowledge Discovery.
700 1 _aShi, Yinghuan.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aSuk, Heung-Il.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aLiu, Mingxia.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030009182
776 0 8 _iPrinted edition:
_z9783030009205
830 0 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
_x3004-9954 ;
_v11046
856 4 0 _uhttps://doi.org/10.1007/978-3-030-00919-9
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
942 _cSPRINGER
999 _c175369
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