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020 _a9783030120290
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024 7 _a10.1007/978-3-030-12029-0
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072 7 _aCOM016000
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082 0 4 _a006.37
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245 1 0 _aStatistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges
_h[electronic resource] :
_b9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers /
_cedited by Mihaela Pop, Maxime Sermesant, Jichao Zhao, Shuo Li, Kristin McLeod, Alistair Young, Kawal Rhode, Tommaso Mansi.
250 _a1st ed. 2019.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2019.
300 _aXIV, 487 p. 216 illus., 192 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 ;
_v11395
505 0 _aCardiac imaging and image processing -- Machine learning applied to cardiac imaging and image analysis -- Atlas construction -- Statistical modelling of cardiac function across different patient populations -- Cardiac computational physiology -- Model customization -- Atlas based functional analysis -- Ontological schemata for data and results -- Integrated functional and structural analyses -- Pre-clinical and clinical applicability of these methods.
520 _aThis book constitutes the thoroughly refereed post-workshop proceedings of the 9th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges, STACOM 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018. The 52 revised full workshop papers were carefully reviewed and selected from 60 submissions. The topics of the workshop included: cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analyses, as well as the pre-clinical and clinical applicability of these methods.
650 0 _aComputer vision.
650 0 _aArtificial intelligence.
650 0 _aComputer networks .
650 0 _aData mining.
650 1 4 _aComputer Vision.
650 2 4 _aArtificial Intelligence.
650 2 4 _aComputer Communication Networks.
650 2 4 _aData Mining and Knowledge Discovery.
700 1 _aPop, Mihaela.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aSermesant, Maxime.
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_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aZhao, Jichao.
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_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aLi, Shuo.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aMcLeod, Kristin.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aYoung, Alistair.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aRhode, Kawal.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aMansi, Tommaso.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030120283
776 0 8 _iPrinted edition:
_z9783030120306
830 0 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
_x3004-9954 ;
_v11395
856 4 0 _uhttps://doi.org/10.1007/978-3-030-12029-0
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
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942 _cSPRINGER
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