Welcome

Statistical Atlases and Computational Modeling of the Heart (STACOM) workshop has been running annually at MICCAI since 2010. The 8th edition of STACOM workshop will be held on 10 or 14 September 2017, with a scope to create a collaborative forum for young/senior researchers (engineers, biophysicists, mathematicians) and clinicians, working on: statistical analysis of cardiac morphology and dynamics, computational modelling of the heart and fluid dynamics, data/models sharing, personalisation of cardiac electro-mechanical models, quantitative image analysis and translational methods into clinical practice.

The STACOM 2017 workshop accepts regular paper submission describing new methods in the following (not limited) topics:

  • Statistical analysis of cardiac morphology and morphodynamics
  • Computational modeling and simulation of the heart and the great vessels
  • Personalisation of cardiac model, electrophysiology and mechanics
  • Quantitative cardiac image analysis
  • Sharing and reusing cardiac model repository
  • Translational studies of cardiac image analysis in clinical practice

In this edition, the workshop also holds two challenges:

  • Multi-Modality Whole Heart Segmentation (MM-WHS)
  • Automated Cardiac Diagnosis Challenge (ACDC)

MICCAI logo

Key dates

19 June 2017 Abstract submission
1 July 2017 Paper submission
24 July 2017 Notification of acceptance
31 July 2017 Camera ready
10 September 2017 Workshop (full-day)

PROGRAM

Schedule

8:50-9:00 Welcome & opening remarks
9:00-10:00 Keynote (Prof. Kaleem Siddiqi)
10:00-10:30 Coffee break & poster viewing
10:30-11:45 Regular papers
11:45-13:45 Lunch & poster viewing + judging
13:45-15:30 MM-WHS challenge
15:30-16:00 Coffee break
16:00-18:00 ACDC challenge
18:00-18:15 Prizes, final remarks & adjourn

For poster presenter: maximum width is 90cm.

Keynote Speaker

Prof. Kaleem Siddiqi

McGill University, Canada

From Mechanics to Electrical Conduction: Why are Heart Wall Myofibers Helicoidal?

The mammalian heart must function as an efficient pump while simultaneously conducting electrical signals to drive the contraction process. In the ventricles, electrical activation begins at the insertion points of the Purkinje network in the endocardium. How does the diffusion component of the subsequent excitation wave propagate from the endocardium in a healthy heart wall without creating potentially deadly arrhythmias? We close this gap between mechanical and electrical requirements by showing that the heart's pumping architecture is also an ideal conductive medium. Going beyond considerations from mechanics we show that the helicoidal arrangement of myocytes minimizes the directional biases that could lead to aberrant propagation, thereby explaining how electrophysiological principles are consistent with local measurements of cardiac fiber geometry.

Biography: Kaleem Siddiqi received his BS degree from Lafayette College in 1988 and his MS and PhD degrees from Brown University in 1990 and 1995, respectively, all in the field of electrical engineering. He is currently a Professor of Computer Science, an associate member of the Department of Mathematics and Statistics and a member of the Centre for Intelligent Machines at McGill University. He also serves as Director of McGill's NSERC CREATE Program in Medical Image Analysis. Before moving to McGill in 1998, he was a postdoctoral associate in the Department of Computer Science at Yale University (1996-1998) and held a visiting position in the Department of Electrical Engineering at McGill University (1995-1996). His research interests are in computer vision, image analysis, medical imaging and applied mathematics in biology.

FULL PROGRAM

8:50-9:00 Welcome & opening remarks from the event organizers

9:00-10:00 Keynote lecture (Session Chair: Dr. Mihaela Pop)

Prof. Dr. Kaleem Siddiqi, McGill University
"From Mechanics to Electrical Conduction: Why are Heart Wall Myofibers Helicoidal?"

10:00-10:30 Coffee break & poster viewing

10:30-11:45 Regular papers (Session Chairs: Dr. Maxime Sermesant & Dr. Alistair Young)

  • 10:30-10:50 Esther Puyol-Anton, Matthew Sinclair, Bernhard Gerber, Mihaela Silvia Amzulescu, Helene Langet, Mathieu De Craene, Paul Aljabar, Julia Schnabel, Paolo Piro, Andrew P. King: Multiview Machine Learning Using an Atlas of Cardiac Cycle Motion
  • 10:50-11:10 Ilkay Oksuz, Rohan Dharmakumar, Sotirios A. Tsaftaris: Joint Myocardial Registration and Segmentation of Cardiac BOLD MRI
  • 11:10-11:30 Cheng Jin, Heng Yu, Jianjiang Feng, Lei Wang, Jiwen Lu, Jie Zhou: Detection of Substances in the Left Atrial Appendage by Spatiotemporal Motion Analysis Based on 4D-CT

11:30-11:45 Poster teasers from regular papers

11:45-13:45 Lunch & Viewing and judging of posters (see list below)

13:45-15:30 MM-WHS challenge (Session Chairs: Dr. Xiahai Zhuang & Dr. Guang Yang)

  • 13:45-14:00: MM-WHS presentation of data and challenge from the organizers
  • 14:00-14:15: Christian Payer, Darko Stern, Horst Bischof, Martin Urschler: Multi-Label Whole Heart Segmentation Using CNNs and Anatomical Label Configurations
  • 14:15-14:30: Mattias Heinrich, Julien Oster: MRI Whole Heart Segmentation using Discrete Nonlinear Registration and Fast Non-Local Fusion
  • 14:30-14:45: Aliasghar Mortazi, Jeremy Burt, Ulas Bagci: Multi-View Deep Segmentation Networks for Cardiac Substructures from MRI and CT
  • 14:45-15:00: Xin Yang, Cheng Bian, Lequan Yu, Dong Ni, Pheng-Ann Heng: Hybrid Loss Guided Convolutional Networks for Whole Heart Parsing
  • 15:00-15:15: Chunliang Wang, Orjan Smedby: Automatic Whole Heart Segmentation Using Deep Learning and Shape Context
  • 15:15-15:30: Gaetan Galisot, Thierry Brouard, Jean-Yves Ramel: Local probabilistic atlases and a posteriori correction for the segmentation of heart images

15:30-16:00 Coffee break

16:00-18:00 ACDC challenge (Session Chair: Dr. Olivier Bernard)

  • 16:00 - 16:15: Dr. Alain Lalande - Presentation of the ACDC dataset
  • 16:15 - 16:30: Fabian Isensee, Paul F. Jaeger, Peter M. Full, Ivo Wolf, Sandy Engelhardt, Klaus H. Maier-Hein; Automatic Cardiac Disease Assessment on cine-MRI via Time-Series Segmentation and Domain Specific Features
  • 16:30 - 16:45 : Irem Cetin, Gerard Sanroma, Steffen E. Petersen, Sandy Napel, Oscar Camara, Miguel-Angel Gonzalez Ballester, Karim Lekadir: A Radiomics Approach to Computer-Aided Diagnosis with Cardiac Cine-MRI
  • 16:45 - 17:00: Jelmer M. Wolterink, Tim Leiner, Max A. Viergever, Ivana Isgum: Automatic Segmentation and Disease Classification Using Cardiac Cine MR Images
  • 17:00 - 17:15: Mahendra Khened, Varghese Alex, Ganapathy Krishnamurthi: Densely Connected Fully Convolutional Network for Short-Axis Cardiac Cine MR Image Segmentation and Heart Diagnosis using,Random Forest
  • 17:15 - 17:30: Clement Zotti, Zhiming Luo, Olivier HUMBERT, Alain Lalande, Pierre-Marc Jodoin: GridNet with automatic shape prior registration for automatic MRI cardiac segmentation
  • 17:30 - 17:45: Marc-Michel Rohe, Maxime Sermesant and Xavier Pennec: Automatic Multi-Atlas Segmentation of Myocardium with SVF-Net
  • 17:45 - 18:00: Pierre-Marc Jodoin - Overall results and wrap up of ACDC challenge

18:00-18:15 Prizes, Final remarks and Adjourn

POSTERS

Regular papers

  • Susana Merino-Caviedes, Lucilio Cordero-Grande, M. Teresa Sevilla-Ruiz, Ana Revilla-Orodea, M. Teresa Pérez Rodríguez, César Palencia de Lara, Marcos Martín-Fernández, Carlos Alberola-López: Estimation of Healthy and Fibrotic Tissue Distributions in DE-CMR Incorporating CINE-CMR in an EM Algorithm
  • Mia Mojica, Mihaela Pop, Maxime Sermesant, Mehran Ebrahimi: Multilevel Non-Parametric Groupwise Registration in Cardiac MRI: Application to Explanted Porcine Hearts
  • Antong Chen, Tian Zhou, Ilknur Icke, Sarayu Parimal, Belma Dogdas, Joseph Forbes, Smita Sampath, Ansuman Bagchi, Chih-Liang Chin: Transfer Learning for the Fully Automatic Segmentation of Left Ventricle Myocardium in Porcine Cardiac Cine MR Images
  • Cheng Jin, Heng Yu, Jianjiang Feng, Lei Wang, Jiwen Lu, Jie Zhou: Left Atrial Appendage Neck Modeling for Closure Surgery

ACDC challenge

  • Clement Zotti, Zhiming Luo, Olivier Humbert, Alain Lalande, Pierre-Marc Jodoin: GridNet with Automatic Shape Prior Registration for Automatic MRI Cardiac Segmentation
  • Irem Cetin, Gerard Sanroma, Steffen E. Petersen, Sandy Napel, Oscar Camara, Miguel-Ángel González Ballester, Karim Lekadir: A Radiomics Approach to Computer-Aided Diagnosis in Cardiac Cine-MRI
  • Georgios Tziritas, Elias Grinias: Fast Fully-Automatic Localization of Left Ventricle and Myocardium in MRI using MRF Model Optimization, Substructures Tracking and B-spline Smoothing
  • Jelmer M Wolterink, Tim Leiner, Max. A Viergever, Ivana Isgum: Automatic Segmentation and Disease Classification Using Cardiac Cine MR Images          
  • Christian Baumgartner, Lisa Margret Koch, Marc Pollefeys, Ender Konukoglu: An Exploration of 2D and 3D Deep Learning Techniques for Cardiac MR Image Segmentation
  • Fabian Isensee, Paul Jaeger, Peter Full, Ivo Wolf, Sandy Engelhardt, Klaus H. Maier-Hein: Automatic Cardiac Disease Assessment on cine-MRI via Time-Series Segmentation and Domain Specific Features
  • Jay Patravali, Shubham Jain, Sasank Chilamkurthy: 2D-3D Fully Convolutional Neural Networks for Cardiac MR Segmentation
  • Mahendra Khened, Varghese Alex, Ganapathy Krishnamurthi: Densely Connected Fully Convolutional Network for Short-Axis Cardiac Cine MR Image Segmentation and Heart Diagnosis using Random Forest
  • Xin Yang, Cheng Bian, Lequan Yu, Dong Ni, Pheng-Ann Heng: Class-balanced Deep Neural Network for Automatic Ventricular Structure Segmentation
  • Yeonggul Jang, seongmin ha, Sekeun Kim, Yoonmi Hong, Hyuk-Jae Chang: Automatic Segmentation of LV and RV in Cardiac MRI
  • Marc-Michel Rohé, Maxime Sermesant, Xavier Pennec: Automatic Multi-Atlas Segmentation of Myocardium with SVF-Net

MM-WHS challenge

  • Xin Yang, Cheng Bian, Lequan Yu, Dong Ni, Pheng-Ann Heng: 3D Convolutional Networks for Fully Automatic Fine-grained Whole Heart Partition
  • Christian Payer, Darko Stern, Horst Bischof, Martin Urschler: Multi-Label Whole Heart Segmentation Using CNNs and Anatomical Label Configurations
  • Aliasghar Mortazi, Jeremy Burt, Ulas Bagci: Multi-Planar Deep Segmentation Networks for Cardiac Substructures from MRI and CT
  • Gaetan Galisot, Thierry Brouard, Jean-Yves Ramel: Local Probabilistic Atlases and A Posteriori Correction for the Segmentation of Heart Images
  • Xin Yang, Cheng Bian, Lequan Yu, Dong Ni, Pheng Ann Heng: Hybrid Loss Guided Convolutional Networks for Whole Heart Parsing
  • Qianqian Tong, Munan Ning, Weixin Si, Xiangyun Liao, Jing Qin: 3D Deeply-Supervised U-Net based Whole Heart Segmentation
  • Mattias Heinrich, Julien Oster: MRI Whole Heart Segmentation using Discrete Nonlinear Registration and Fast Non-Local Fusion
  • Chunliang Wang, Örjan Smedby: Automatic Whole Heart Segmentation Using Deep Learning and Shape Context
  • Guanyu Yang, Chenchen Sun, Yang Chen, Lijun Tabg, Huazhong Shu, Jean-Louis Dillenseger: Automatic Whole Heart Segmentation in CT Images Based on Multi-atlas Image Registration

PAPER SUBMISSION

Submit Your Paper

The STACOM 2016 workshop will accept 8-page papers (LNCS-Springer format) as regular submissions or challenges. Note that there are different rules prior paper submission for the challenges. Please refer to specific guidelines from the challenge website. Selected papers will be published in a Lecture Notes in Computer Science proceeding published by Springer (see previous STACOM proceedings).

CHALLENGES

Multi-Modality Whole Heart Segmentation

Segmentation and registration of whole heart images are still challenging. The extraction and modeling of whole heart substructures currently relies heavily on manual delineation, which is a time-consuming task and it is also prone to errors and dependent on the expertise of the observer. The task is to automatically delineate the whole heart from both cardiac CT and cardiac MRI data. 60 cardiac CT/CTA and 50+ cardiac MRI volumes in 3D volumes that cover the whole heart are provided. This challenge is organized by Xiahai Zhuang (Fudan University, China), Guang Yang (Imperial College London, UK) and Lei Li (Shanghai Jiao Tong University, China).

Automated Cardiac Diagnosis Challenge

The goal of this contest is two-fold:

  1. Compare the performance of automatic methods on the segmentation of the left ventricular endocardium and epicardium as the right ventricular endocardium for both end diastolic and end systolic phase instances
  2. Compare the performance of automatic methods for the classification of the examinations in five classes (normal case, heart failure with infarction, dilated cardiomyopathy, hypertrophic cardiomyopathy, abnormal right ventricle)

The challenge data is composed by 150 patients with cine-MR images acquired in clinical routine. This challenge is organized by Pierre-Marc Jodoin (University of Sherbrooke, Canada), Alain Lalande (University of Bourgogne, France), and Olivier Bernard (University of Lyon, France).

ORGANIZERS

Alistair Young

University of Auckland, New Zealand

Mihaela Pop

University of Toronto, Canada

Maxime Sermesant

Asclepios INRIA, France

Tommaso Mansi

Siemens Healthcare, Medical Imaging Technologies, USA

Kawal Rhode

King's College London, United Kingdom

Kristin McLeod

Simula Research Laboratory, Norway

Xiahai Zhuang

Fudan University, China

Guang Yang

Imperial College London, UK

Lei Li

Shanghai Jiao Tong University, China

Pierre-Marc Jodoin

University of Sherbrooke, Canada

Alain Lalande

University of Bourgogne, France

Olivier Bernard

University of Lyon, France

Avan Suinesiaputra

University of Auckland, New Zealand