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Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers

14th International Workshop, STACOM 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Revised Selected Papers

  • Conference proceedings
  • © 2024

Overview

Editors:
  1. Oscar Camara

    1. Universitat Pompeu Fabra, Barcelona, Spain

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  2. Esther Puyol-Antón

    1. King's College London, London, UK

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  3. Maxime Sermesant

    1. Inria, Sophia Antipolis, France

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  4. Avan Suinesiaputra

    1. King's College London, London, UK

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  5. Qian Tao

    1. Technische Universiteit Delft, Delft, The Netherlands

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  6. Chengyan Wang

    1. Fudan University, Shanghai, China

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  7. Alistair Young

    1. King's College London, London, UK

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14507)

Included in the following conference series:

Conference proceedings info: STACOM 2023.

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About this book

​This book constitutes the proceedings of the 14th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2023, as well as the Cardiac MRI Reconstruction Challenge, CMRxRecon Challenge. 

There was a total of 53 submissions to the workshop. 

The 24 regular workshop papers included in this volume were carefully reviewed and selected from 29 paper submissions. They deal with cardiac segmentation, modelling, strain quantification, registration, statistical shape analysis, and quality control. 

Keywords

Table of contents (45 papers)

  1. Front Matter

    Pages i-xiv
    Download chapter PDF

  2. Regular Papers

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. CardiacSeg: Customized Pre-training Volumetric Transformer with Scaling Pyramid for 3D Cardiac Segmentation

      • Zhiyu Ye, Hairong Zheng, Tong Zhang
      Pages 3-14

    3. Voxel2Hemodynamics: An End-to-End Deep Learning Method for Predicting Coronary Artery Hemodynamics

      • Ziyu Ni, Linda Wei, Lijian Xu, Qing Xia, Hongsheng Li, Shaoting Zhang et al.
      Pages 15-24

    4. Deep Learning for Automatic Strain Quantification in Arrhythmogenic Right Ventricular Cardiomyopathy

      • Laura Alvarez-Florez, Jörg Sander, Mimount Bourfiss, Fleur V. Y. Tjong, Birgitta K. Velthuis, Ivana Išgum
      Pages 25-34

    5. Patient Stratification Based on Fast Simulation of Cardiac Electrophysiology on Digital Twins

      • Dolors Serra, Pau Romero, Miguel Lozano, Ignacio Garcia-Fernandez, Diego Penela, Antonio Berruezo et al.
      Pages 35-43

    6. Deep Conditional Shape Models for 3D Cardiac Image Segmentation

      • Athira J. Jacob, Puneet Sharma, Daniel Ruckert
      Pages 44-54

    7. Global Sensitivity Analysis of Thrombus Formation in the Left Atrial Appendage of Atrial Fibrillation Patients

      • Zineb Smine, Paolo Melidoro, Ahmed Qureshi, Stefano Longobardi, Steven E. Williams, Oleg Aslanidi et al.
      Pages 55-65

    8. Sparse Annotation Strategies for Segmentation of Short Axis Cardiac MRI

      • Josh Stein, Maxime Di Folco, Julia A. Schnabel
      Pages 66-76

    9. Contrast-Agnostic Groupwise Registration by Robust PCA for Quantitative Cardiac MRI

      • Xinqi Li, Yi Zhang, Yidong Zhao, Jan van Gemert, Qian Tao
      Pages 77-87

    10. FM-Net: A Fully Automatic Deep Learning Pipeline for Epicardial Adipose Tissue Segmentation

      • Fan Feng, Carl-Johan Carlhäll, Yongyao Tan, Shaleka Agrawal, Peter Lundberg, Jieyun Bai et al.
      Pages 88-97

    11. Automated Quality-Controlled Left Heart Segmentation from 2D Echocardiography

      • Bram W. M. Geven, Debbie Zhao, Stephen A. Creamer, Joshua R. Dillon, Gina M. Quill, Nicola C. Edwards et al.
      Pages 98-107

    12. Impact of Hypertension on Left Ventricular Pressure-Strain Loop Characteristics and Myocardial Work

      • Stephen A. Creamer, Debbie Zhao, Gina M. Quill, Abdallah I. Hasaballa, Vicky Y. Wang, Thiranja P. Babarenda Gamage et al.
      Pages 108-118

    13. Automated Segmentation of the Right Ventricle from 3D Echocardiography Using Labels from Cardiac Magnetic Resonance Imaging

      • Joshua R. Dillon, Debbie Zhao, Thiranja P. Babarenda Gamage, Gina M. Quill, Vicky Y. Wang, Nicola C. Edwards et al.
      Pages 119-129

    14. Neural Implicit Functions for 3D Shape Reconstruction from Standard Cardiovascular Magnetic Resonance Views

      • Marica Muffoletto, Hao Xu, Yiyang Xu, Steven E Williams, Michelle C Williams, Karl P Kunze et al.
      Pages 130-139

    15. Deep Learning-Based Pulmonary Artery Surface Mesh Generation

      • Nina Krüger, Jan Brüning, Leonid Goubergrits, Matthias Ivantsits, Lars Walczak, Volkmar Falk et al.
      Pages 140-151Open Access

    16. Impact of Catheter Orientation on Cardiac Radiofrequency Ablation

      • Massimiliano Leoni, Argyrios Petras, Zoraida Moreno Weidmann, Jose M. Guerra, Luca Gerardo-Giorda
      Pages 152-162

    17. Generating Virtual Populations of 3D Cardiac Anatomies with Snowflake-Net

      • Jiachuan Peng, Marcel Beetz, Abhirup Banerjee, Min Chen, Vicente Grau
      Pages 163-173

    18. Effects of Fibrotic Border Zone on Drivers for Atrial Fibrillation: An In-Silico Mechanistic Investigation

      • Shaheim Ogbomo-Harmitt, George Obada, Nele Vandersickel, Andrew P. King, Oleg Aslanidi
      Pages 174-185

    19. Exploring the Relationship Between Pulmonary Artery Shape and Pressure in Pulmonary Hypertension: A Statistical Shape Analysis Study

      • Malak Sabry, Uxio Hermida, Ahmed Hassan, Michael Nagy, David Stojanovski, Irini Samuel et al.
      Pages 186-195
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Other volumes

  1. Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers

Editors and Affiliations

  • Universitat Pompeu Fabra, Barcelona, Spain

    Oscar Camara

  • King's College London, London, UK

    Esther Puyol-Antón, Avan Suinesiaputra, Alistair Young

  • Inria, Sophia Antipolis, France

    Maxime Sermesant

  • Technische Universiteit Delft, Delft, The Netherlands

    Qian Tao

  • Fudan University, Shanghai, China

    Chengyan Wang

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