Abstract
Stochastically evolving geometric systems are studied in shape analysis and computational anatomy for modeling random evolutions of human organ shapes. The notion of geodesic paths between shapes is central to shape analysis and has a natural generalization as diffusion bridges in a stochastic setting. Simulation of such bridges is key to solving inference and registration problems in shape analysis. We demonstrate how to apply state-of-the-art diffusion bridge simulation methods to recently introduced stochastic shape deformation models, thereby substantially expanding the appli-cability of such models. We exemplify these methods by estimating template shapes from observed shape configurations while simultaneously learning model parameters.
Original language | English |
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Pages (from-to) | 293-323 |
Number of pages | 31 |
Journal | SIAM Journal on Imaging Sciences |
Volume | 15 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2022 |
Keywords
- bridge simulation
- conditional diffusion
- guided proposals
- hypoelliptic diffusion
- landmark dynamics
- shape analysis
- shape matching