Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges (häftad)
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Format
Häftad (Paperback / softback)
Språk
Engelska
Antal sidor
487
Utgivningsdatum
2019-02-14
Upplaga
1st ed. 2019
Förlag
Springer Nature Switzerland AG
Medarbetare
Young, Alistair (red.)/Rhode, Kawal (red.)/Mansi, Tommaso (red.)
Illustrationer
192 Illustrations, color; 24 Illustrations, black and white; XIV, 487 p. 216 illus., 192 illus. in c
Dimensioner
234 x 156 x 26 mm
Vikt
699 g
Antal komponenter
1
Komponenter
1 Paperback / softback
ISBN
9783030120283

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Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges (häftad)

Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges

9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers

av Mihaela Pop, Maxime Sermesant, Jichao Zhao, Shuo Li, Kristin McLeod
Häftad Engelska, 2019-02-14
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This 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.
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Fler böcker av författarna

Mihaela Pop, Maxime Sermesant, Jichao Zhao, Shuo Li, Kristin McLeod

Innehållsförteckning

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.- Pre-clinical and clinical applicability of these methods.