The Statistical Atlases and Computational Modeling of the Heart (STACOM) workshop has been running annually at MICCAI since 2010. The 16th edition of STACOM workshop is going to be held in conjunction with the MICCAI 2025 in Daejeon, Republic of Korea. The STACOM workshop is aiming 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.
Keynote speaker
Hyun Jin Kim, Associate Professor at the Department of Mechanical Engineering at the Korea Advanced Institute of Science and Technology
Title: Biomechanics modeling enhanced by AI
Abstract: Image-based modeling of the cardiovascular system has advanced significantly over the past few decades and is now widely used as a diagnostic, evaluative, and predictive tool for cardiovascular diseases. However, achieving full personalization in image-based models remains challenging due to the high uncertainty associated with many biomechanical parameters. While invasive measurements are typically used, the limited availability of such data often necessitates the use of physics- or data-driven methods. In this talk, I will provide an overview of image-based modeling approaches with a focus on coronary artery disease, highlighting efforts to personalize model parameters and account for their uncertainties.
Short bio: Hyun Jin Kim is an associate professor in the Department of Mechanical Engineering at the Korea Advanced Institute of Science and Technology. Prior to joining KAIST, she worked for a decade as a senior research engineer at HeartFlow, Inc., where she developed software for diagnosing coronary artery disease and assessing the rupture risk of coronary plaques. Her research currently focuses on advancing a variety of computational methods to assess the severity of cardiovascular diseases, predict disease progression, and evaluate medical devices using mechanics- and data-driven approaches.
Challenges
CMRxRecon2025 Challenge
The objective of establishing the CMRx series challenges is to provide a benchmark that enables the research community to contribute to the work of accelerated CMR imaging with universal approaches that allow more diverse applications and better performance in real-world deployment in various environments. The previous CMRxRecon2023 and CMRxRecon2024 dataset did not cover multi-center, multi-vendor, and multiple diseases. Therefore, this year we aim to make an important leap towards real-world clinical scenarios.
For more information to join the challenge: click here