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Record Nr. |
UNISA996466443503316 |
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Titolo |
Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges [[electronic resource] ] : 9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers / / edited by Mihaela Pop, Maxime Sermesant, Jichao Zhao, Shuo Li, Kristin McLeod, Alistair Young, Kawal Rhode, Tommaso Mansi |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
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ISBN |
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Edizione |
[1st ed. 2019.] |
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Descrizione fisica |
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1 online resource (XIV, 487 p. 216 illus., 192 illus. in color.) |
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Collana |
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Image Processing, Computer Vision, Pattern Recognition, and Graphics ; ; 11395 |
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Disciplina |
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Soggetti |
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Optical data processing |
Artificial intelligence |
Computer communication systems |
Data mining |
Image Processing and Computer Vision |
Artificial Intelligence |
Computer Communication Networks |
Data Mining and Knowledge Discovery |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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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. |
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Sommario/riassunto |
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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 |
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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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