@article{1443815,
      recid = {1443815},
      author = {Puyol Anton, Esther, and Pop, Mihaela and Martín-Isla,  Carlos, and Sermesant, Maxime, and Suinesiaputra, Avan, and  Camara, Oscar and Lekadir, Karim, and Young, Alistair},
      title = {Statistical atlases and computational models of the heart  : multi-disease, multi-view, and multi-center right  ventricular segmentation in cardiac MRI challenge : 12th  International Workshop, STACOM 2021, held in conjunction  with MICCAI 2021, Strasbourg, France, September 27, 2021,  Revised selected papers /. STACOM (Workshop)},
      pages = {1 online resource (xiii, 385 pages) :},
      note = {"STACOM 2021, was held as a virtual event."-- Preface.},
      abstract = {This book constitutes the proceedings of the 12th  International Workshop on Statistical Atlases and  Computational Models of the Heart, STACOM 2021, as well as  the M&Ms-2 Challenge: Multi-Disease, Multi-View and  Multi-Center Right Ventricular Segmentation in Cardiac MRI  Challenge. The 25 regular workshop papers included in this  volume were carefully reviewed and selected after being  revised. They deal with cardiac imaging and image  processing, machine learning applied to cardiac imaging and  image analysis, atlas construction, artificial  intelligence, 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. In addition, 15 papers from the M&MS-2 challenge  are included in this volume. The Multi-Disease, Multi-View  & Multi-Center Right Ventricular Segmentation in Cardiac  MRI Challenge (M&Ms-2) is focusing on the development of  generalizable deep learning models for the Right Ventricle  that can maintain good segmentation accuracy on different  centers, pathologies and cardiac MRI views. There was a  total of 48 submissions to the workshop.},
      url = {http://library.usi.edu/record/1443815},
      doi = {https://doi.org/10.1007/978-3-030-93722-5},
}