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

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 statistical atlases
• image analysis
• atrial segmentation
• left ventricle quantification
• electrophysiology modeling
• heart biomechanical simulations
• CFD
• neural networks
• deep learning
• image processing
• artificial intelligence
• image segmentation
• segmentation methods
• SVM
• medical images
• image reconstruction
• cross validation
• image quality
• wireless networks
• automatic segmentations

• University of Toronto, Toronto, Canada

  Mihaela Pop

• Inria, Epione Group, Sophia-Antipolis, France

  Maxime Sermesant

• Auckland University, Auckland, New Zealand

  Jichao Zhao

• University of Western Ontario, London, Canada

  Shuo Li

• GE Healthcare, Oslo, Norway

  Kristin McLeod

• King’s College London, London, UK

  Alistair Young, Kawal Rhode

• Siemens Medical Solutions USA, Inc., Princeton, USA

  Tommaso Mansi

Policies and ethics