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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

  • Conference proceedings
  • © 2019

Overview

Editors:
  1. Mihaela Pop

    1. University of Toronto, Toronto, Canada

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  2. Maxime Sermesant

    1. Inria, Epione Group, Sophia-Antipolis, France

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  3. Jichao Zhao

    1. Auckland University, Auckland, New Zealand

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  4. Shuo Li

    1. University of Western Ontario, London, Canada

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  5. Kristin McLeod

    1. GE Healthcare, Oslo, Norway

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  6. Alistair Young

    1. King’s College London, London, UK

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  7. Kawal Rhode

    1. King’s College London, London, UK

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  8. Tommaso Mansi

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

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11395)

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

Included in the following conference series:

Conference proceedings info: STACOM 2018.

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Table of contents (51 papers)

  1. Front Matter

    Pages I-XIV
    Download chapter PDF

  2. Regular Papers

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Estimating Sheets in the Heart Wall

      • Tabish A. Syed, Babak Samari, Kaleem Siddiqi
      Pages 3-11

    3. Automated Motion Correction and 3D Vessel Centerlines Reconstruction from Non-simultaneous Angiographic Projections

      • Abhirup Banerjee, Rajesh K. Kharbanda, Robin P. Choudhury, Vicente Grau
      Pages 12-20

    4. Left Ventricle Segmentation and Quantification from Cardiac Cine MR Images via Multi-task Learning

      • Shusil Dangi, Ziv Yaniv, Cristian A. Linte
      Pages 21-31

    5. Statistical Shape Clustering of Left Atrial Appendages

      • Jakob M. Slipsager, Kristine A. Juhl, Per E. Sigvardsen, Klaus F. Kofoed, Ole De Backer, Andy L. Olivares et al.
      Pages 32-39

    6. Deep Learning Segmentation of the Left Ventricle in Structural CMR: Towards a Fully Automatic Multi-scan Analysis

      • Hakim Fadil, John J. Totman, Stephanie Marchesseau
      Pages 40-48

    7. Cine and Multicontrast Late Enhanced MRI Registration for 3D Heart Model Construction

      • Fumin Guo, Mengyuan Li, Matthew Ng, Graham Wright, Mihaela Pop
      Pages 49-57

    8. Joint Analysis of Personalized In-Silico Haemodynamics and Shape Descriptors of the Left Atrial Appendage

      • Jordi Mill, Andy L. Olivares, Etelvino Silva, Ibai Genua, Alvaro Fernandez, Ainhoa Aguado et al.
      Pages 58-66

    9. How Accurately Does Transesophageal Echocardiography Identify the Mitral Valve?

      • Claire Vannelli, Wenyao Xia, John Moore, Terry Peters
      Pages 67-76

    10. Stochastic Model-Based Left Ventricle Segmentation in 3D Echocardiography Using Fractional Brownian Motion

      • Omar S. Al-Kadi, Allen Lu, Albert J. Sinusas, James S. Duncan
      Pages 77-84

    11. Context Aware 3D Fully Convolutional Networks for Coronary Artery Segmentation

      • Yongjie Duan, Jianjiang Feng, Jiwen Lu, Jie Zhou
      Pages 85-93

    12. Learning Associations Between Clinical Information and Motion-Based Descriptors Using a Large Scale MR-derived Cardiac Motion Atlas

      • Esther Puyol-Antón, Bram Ruijsink, Hélène Langet, Mathieu De Craene, Paolo Piro, Julia A. Schnabel et al.
      Pages 94-102

    13. Computational Modelling of Electro-Mechanical Coupling in the Atria and Its Changes During Atrial Fibrillation

      • Sofia Monaci, David Nordsletten, Oleg Aslanidi
      Pages 103-113

    14. High Throughput Computation of Reference Ranges of Biventricular Cardiac Function on the UK Biobank Population Cohort

      • Rahman Attar, Marco Pereañez, Ali Gooya, Xènia Albà, Le Zhang, Stefan K. Piechnik et al.
      Pages 114-121

    15. Lumen Segmentation of Aortic Dissection with Cascaded Convolutional Network

      • Ziyan Li, Jianjiang Feng, Zishun Feng, Yunqiang An, Yang Gao, Bin Lu et al.
      Pages 122-130

    16. A Vessel-Focused 3D Convolutional Network for Automatic Segmentation and Classification of Coronary Artery Plaques in Cardiac CTA

      • Jiang Liu, Cheng Jin, Jianjiang Feng, Yubo Du, Jiwen Lu, Jie Zhou
      Pages 131-141

    17. Semi-automated Image Segmentation of the Midsystolic Left Ventricular Mitral Valve Complex in Ischemic Mitral Regurgitation

      • Ahmed H. Aly, Abdullah H. Aly, Mahmoud Elrakhawy, Kirlos Haroun, Luis Prieto-Riascos, Robert C. Gorman Jr. et al.
      Pages 142-151

    18. Atrial Scar Segmentation via Potential Learning in the Graph-Cut Framework

      • Lei Li, Guang Yang, Fuping Wu, Tom Wong, Raad Mohiaddin, David Firmin et al.
      Pages 152-160

    19. 4D Cardiac Motion Modeling Using Pair-Wise Mesh Registration

      • Siyeop Yoon, Stephen Baek, Deukhee Lee
      Pages 161-170
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  1. Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges

Keywords

About this book

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.

Editors and Affiliations

  • 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

Bibliographic Information

  • Book Title: Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges

  • Book Subtitle: 9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers

  • Editors: Mihaela Pop, Maxime Sermesant, Jichao Zhao, Shuo Li, Kristin McLeod, Alistair Young, Kawal Rhode, … Tommaso Mansi

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-030-12029-0

  • Publisher: Springer Cham

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

  • Copyright Information: Springer Nature Switzerland AG 2019

  • Softcover ISBN: 978-3-030-12028-3Published: 14 February 2019

  • eBook ISBN: 978-3-030-12029-0Published: 05 March 2019

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XIV, 487

  • Number of Illustrations: 24 b/w illustrations, 192 illustrations in colour

  • Topics: Image Processing and Computer Vision, Artificial Intelligence, Computer Communication Networks, Data Mining and Knowledge Discovery

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