Statistical Atlases and Computational Modeling of the Heart (STACOM) workshop has been running annually at MICCAI since 2010. The 7th edition of STACOM workshop will be held on 17th October 2016, 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 2016 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



Key dates

15 May Submission site open
27 June Abstract submission
30 June Paper submission
15 July Notification of acceptance
1 August Camera ready
17 October Workshop (full-day)


8:30-9:00 Registration & Welcome
9:00-10:00 Keynote 1
10:00-10:30 Poster teasers from regular papers
10:30-11:00 Coffee break
11:00-12:00 Challenge
12:00-13:00 Posters (viewing & judging)
13:00-14:00 Lunch
14:00-15:00 Keynote 2
15:00-16:00 3 regular papers
16:00-16:30 Coffee breaks
16:30-17:10 2 regular papers
17:10-17:30 Closing remarks, prizes & adjourn


Keynote Speakers

Dr. Sophie Mavrogeni (MD, FESC)

Onassis Cardiac Surgery Center, Athens, Greece

Cardiovascular Magnetic Resonance: Current status and future applications

Currently, Cardiac MRI is the ideal technique for cardiovascular morphology, function, tissue characterisation, myocardial inflammation, perfusion and fibrosis assessment. We expect that in near future Cardiac MRI will allow to detect early pathophysiologic changes at molecular level.

Prof. Dr. Dimitris Metaxas

Rutgers University, USA

Model-based Large Scale Cardiac Analytics

Over the last 20 years, we have been developing a general, scalable, computational framework that combines principles of deformable models, computational learning, sparse methods and mixed norms. This framework has been used for resolution of complex large scale cardiac analytics. We will present this framework and its application to cardiac analytics which include feature discovery for segmentation and 3D reconstruction of the cardiac chambers, cardiac MRI image reconstruction from sparse data, 3D spatiotemporal wall and blood flow analytics from CT. Finally, we will show quantitative analysis results of various cardiac diseases such as hypertrophy, dysynchrony and infarction.

Submit Your Paper

The STACOM 2016 workshop will accept 8-page papers (LNCS-Springer format), similar to MICCAI guidelines, as regular submissions or for the quantification of atrial wall thickness challenge. Selected papers will be published in a Lecture Notes in Computer Science proceeding published by Springer (see previous STACOM proceedings).


Left Atrium Wall Thickness Challenge

This year STACOM workshop runs a computational challenge to analyse left atrium from cardiac MR and CT images. The dataset is provided by the King's College London in UK. The images included in the challenge consists of MRI (n=10) and CT (n=10) datasets. The MRI images are acquired at 1.4 mm isotropic resolution. The CT images are acquired at 0.5 mm in-plane resolution with a slice thickness of 1 mm. Your task is to quantify wall thickness in the left atrium provided by the images. The challenge is organised by Dr. Rashed Karim.


E-mail stacom@inria.fr for general inquiries
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

Rashed Karim
King's College London, United Kingdom

Avan Suinesiaputra
University of Auckland, New Zealand