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  • Conference proceedings
  • © 2018

Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges

8th International Workshop, STACOM 2017, Held in Conjunction with MICCAI 2017, Quebec City, Canada, September 10-14, 2017, Revised Selected Papers

Editors:

  1. Mihaela Pop

    1. Sunnybrook Research Institute, University of Toronto, Toronto, Canada

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  2. Maxime Sermesant

    1. Inria-Asclepios, Sophia Antipolis, France

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  3. Pierre-Marc Jodoin

    1. Université de Sherbrooke, Quebec City, Canada

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  4. Alain Lalande

    1. University Bourgogne, Dijon, France

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  5. Xiahai Zhuang

    1. Fudan University, Shanghai, China

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  6. Guang Yang

    1. Cardiovascular Research Center, National Heart and Lung Institute, Royal Brompton Hospital, London, United Kingdom

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  7. Alistair Young

    1. University of Auckland, Auckland, New Zealand

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  8. Olivier Bernard

    1. CREATIS, INSA-Lyon, Villeurbanne, France

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10663)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Conference series link(s): STACOM: International Workshop on Statistical Atlases and Computational Models of the Heart

Conference proceedings info: STACOM 2017.

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Table of contents (27 papers)

  1. Front Matter

    Pages I-XIII
    PDF

  2. Regular Papers

    1. Front Matter

      Pages 1-1
      PDF

    2. Multiview Machine Learning Using an Atlas of Cardiac Cycle Motion

      • Esther Puyol-Antón, Matthew Sinclair, Bernhard Gerber, Mihaela Silvia Amzulescu, Hélène Langet, Mathieu De Craene et al.
      Pages 3-11

    3. Joint Myocardial Registration and Segmentation of Cardiac BOLD MRI

      • Ilkay Oksuz, Rohan Dharmakumar, Sotirios A. Tsaftaris
      Pages 12-20

    4. Transfer Learning for the Fully Automatic Segmentation of Left Ventricle Myocardium in Porcine Cardiac Cine MR Images

      • Antong Chen, Tian Zhou, Ilknur Icke, Sarayu Parimal, Belma Dogdas, Joseph Forbes et al.
      Pages 21-31

    5. Left Atrial Appendage Neck Modeling for Closure Surgery

      • Cheng Jin, Heng Yu, Jianjiang Feng, Lei Wang, Jiwen Lu, Jie Zhou
      Pages 32-41

    6. Detection of Substances in the Left Atrial Appendage by Spatiotemporal Motion Analysis Based on 4D-CT

      • Cheng Jin, Heng Yu, Jianjiang Feng, Lei Wang, Jiwen Lu, Jie Zhou
      Pages 42-50

    7. Estimation of Healthy and Fibrotic Tissue Distributions in DE-CMR Incorporating CINE-CMR in an EM Algorithm

      • Susana Merino-Caviedes, Lucilio Cordero-Grande, M. Teresa Sevilla-Ruiz, Ana Revilla-Orodea, M. Teresa Pérez Rodríguez, César Palencia de Lara et al.
      Pages 51-59

    8. Multilevel Non-parametric Groupwise Registration in Cardiac MRI: Application to Explanted Porcine Hearts

      • Mia Mojica, Mihaela Pop, Maxime Sermesant, Mehran Ebrahimi
      Pages 60-69

  3. ACDC Challenge

    1. Front Matter

      Pages 71-71
      PDF

    2. GridNet with Automatic Shape Prior Registration for Automatic MRI Cardiac Segmentation

      • Clément Zotti, Zhiming Luo, Olivier Humbert, Alain Lalande, Pierre-Marc Jodoin
      Pages 73-81

    3. A Radiomics Approach to Computer-Aided Diagnosis with Cardiac Cine-MRI

      • Irem Cetin, Gerard Sanroma, Steffen E. Petersen, Sandy Napel, Oscar Camara, Miguel-Angel Gonzalez Ballester et al.
      Pages 82-90

    5. Automatic Segmentation and Disease Classification Using Cardiac Cine MR Images

      • Jelmer M. Wolterink, Tim Leiner, Max A. Viergever, Ivana Išgum
      Pages 101-110

    6. An Exploration of 2D and 3D Deep Learning Techniques for Cardiac MR Image Segmentation

      • Christian F. Baumgartner, Lisa M. Koch, Marc Pollefeys, Ender Konukoglu
      Pages 111-119

    7. Automatic Cardiac Disease Assessment on cine-MRI via Time-Series Segmentation and Domain Specific Features

      • Fabian Isensee, Paul F. Jaeger, Peter M. Full, Ivo Wolf, Sandy Engelhardt, Klaus H. Maier-Hein
      Pages 120-129

    8. 2D-3D Fully Convolutional Neural Networks for Cardiac MR Segmentation

      • Jay Patravali, Shubham Jain, Sasank Chilamkurthy
      Pages 130-139

    10. Class-Balanced Deep Neural Network for Automatic Ventricular Structure Segmentation

      • Xin Yang, Cheng Bian, Lequan Yu, Dong Ni, Pheng-Ann Heng
      Pages 152-160

    11. Automatic Segmentation of LV and RV in Cardiac MRI

      • Yeonggul Jang, Yoonmi Hong, Seongmin Ha, Sekeun Kim, Hyuk-Jae Chang
      Pages 161-169
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Other Volumes

  1. Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges

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About this book

This book constitutes the thoroughly refereed post-workshop proceedings of the 8th International Workshop on Statistical Atlases and Computational Models of the Heart: ACDC and MMWHS Challenges 2017, held in conjunction with MICCAI 2017, in Quebec, Canada, in September 2017. The 27 revised full workshop papers were carefully reviewed and selected from 35 submissions. The papers cover a wide range of topics computational imaging and modelling of the heart, as well as statistical cardiac atlases. The topics of the workshop included: cardiac imaging and image processing, 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. Besides regular contributing papers, additional efforts of STACOM workshop were also focused on two challenges: ACDC and MM-WHS.

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Keywords

  • artificial intelligence
  • image processing
  • neural networks
  • image segmentation
  • Support Vector Machines SVM
  • machine learning
  • cross-validation
  • segmentation methods
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Editors and Affiliations

  • Sunnybrook Research Institute, University of Toronto, Toronto, Canada

    Mihaela Pop

  • Inria-Asclepios, Sophia Antipolis, France

    Maxime Sermesant

  • Université de Sherbrooke, Quebec City, Canada

    Pierre-Marc Jodoin

  • University Bourgogne, Dijon, France

    Alain Lalande

  • Fudan University, Shanghai, China

    Xiahai Zhuang

  • Cardiovascular Research Center, National Heart and Lung Institute, Royal Brompton Hospital, London, United Kingdom

    Guang Yang

  • University of Auckland, Auckland, New Zealand

    Alistair Young

  • CREATIS, INSA-Lyon, Villeurbanne, France

    Olivier Bernard

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Bibliographic Information

  • Book Title: Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges

  • Book Subtitle: 8th International Workshop, STACOM 2017, Held in Conjunction with MICCAI 2017, Quebec City, Canada, September 10-14, 2017, Revised Selected Papers

  • Editors: Mihaela Pop, Maxime Sermesant, Pierre-Marc Jodoin, Alain Lalande, Xiahai Zhuang, Guang Yang, Alistair Young, … Olivier Bernard

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-319-75541-0

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer International Publishing AG, part of Springer Nature 2018

  • Softcover ISBN: 978-3-319-75540-3Published: 15 March 2018

  • eBook ISBN: 978-3-319-75541-0Published: 14 March 2018

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XIII, 260

  • Number of Illustrations: 94 b/w illustrations

  • Topics: Computer Vision, Artificial Intelligence

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Access via your institution
eBook USD 54.99
Price excludes VAT (USA)
  • ISBN: 978-3-319-75541-0
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book USD 72.00
Price excludes VAT (USA)
Learn about institutional subscriptions