معرفی
Professor Fabrice Heitz serves as Director of the ICube Laboratory at Telecom Physics Strasbourg, University of Strasbourg, where he leads the IMAGeS research team (Images, Modeling, Learning, Geometry and Statistics). His academic career spans several decades with significant leadership roles including Director of LSIIT UMR 7005 CNRS (2005-2012) and Deputy Director of ICube Laboratory (2013-2022).
Professor Heitz's educational background is closely tied to Telecom Physics Strasbourg where he has taught foundational courses including Introduction to Signal Processing, Processing Random Signals, Statistics, and 2D Signal and Image Processing across undergraduate and Master's levels in the Imaging, Robotics, Engineering for the Living program.
His research expertise centers on signal and image processing with specialization in statistical modeling of 3D+t images, Markovian and non-Gaussian models, appearance models, and deformable models. His work in machine learning addresses critical challenges in rigid and deformable registration of multimodal images, 3D image segmentation, 3D+t temporal tracking, and inter-image change detection, with primary applications in medical imaging and time sequence analysis. Current research directions include cryo reconstruction EM, 3D surface modeling, and preoperative planning for ARC needles.
Professor Heitz has established himself as a prominent figure in medical image analysis, with his supervised doctoral research spanning applications from brain MRI analysis to lung CT segmentation. His former students have achieved notable positions at INRIA, Philips, Microsoft, and universities worldwide, demonstrating the impact of his mentorship.
- Director of ICube Laboratory (2023-present)
- Elected member of Research Commission of University of Strasbourg (2021-2025)
- Former Head of IMAGeS team at ICube (2016-2022)
- Associate Editor of IEEE Transactions on Image Processing (1996-1999)
Professor Heitz leads the IMAGeS research team, which brings together experts working at the intersection of image processing, machine learning, geometry, and statistics to develop innovative solutions for medical diagnostics, surgical planning, and other critical applications. His leadership extends to numerous national and international committees including AERES/HCERES expert panels and ANR review boards.
