Conditional LDDMM flow matching: generative shape modeling for domain uncertainty quantification
Abstract
This talk gave a brief overview of ongoing research into the use of a novel generative model for domain shape uncertainty quantification based on conditional LDDMM flow matching, applied to pulsatile flow in the aorta.
Fields of Study & Subjects
Model Reduction and Neural Networks
Medical Image Segmentation Techniques
Elasticity and Material Modeling
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 3 March 2026
- Language
- EN