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 /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Pop, Mihaela (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Sermesant, Maxime (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Zhao, Jichao (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Li, Shuo (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), McLeod, Kristin (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Young, Alistair (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Rhode, Kawal (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Mansi, Tommaso (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Σειρά: Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 11395
• Θέματα: 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.

 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. 

 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.