Conference paper
Advances in geometrical analysis of Topologically-varying shapes
2020 IEEE 17th International Symposium on Biomedical Imaging Workshops (ISBI Workshops)
2020 IEEE 17th International Symposium on Biomedical Imaging Workshops (ISBI Workshops) (Iowa City, IA, USA, 04/04/2020)
2020
Abstract
Statistical shape analysis using geometrical approaches provides comprehensive tools – such as geodesic deformations, shape averages, and principal modes of variability – all in the original object space. While geometrical methods have been limited to objects with fixed topologies (e.g. functions, closed curves, surfaces of genus zero, etc) in the past, this paper summarizes recent progress where geometrical approaches are beginning to handle topologically different objects – trees, graphs, etc – that exhibit arbitrary branching and connectivity patterns. The key idea is to “divide-and-conquer”, i.e. break complex objects into simpler parts and help register these parts across objects. Such matching and quantification require invariant metrics from Riemannian geometry and provide foundational tools for statistical shape analysis.
Details
- Title
- Advances in geometrical analysis of Topologically-varying shapes
- Authors/Creators
- A. Srivastava (Author/Creator) - Florida State UniversityX. Guo (Author/Creator) - Florida State UniversityH. Laga (Author/Creator) - Florida State University
- Publication Details
- 2020 IEEE 17th International Symposium on Biomedical Imaging Workshops (ISBI Workshops)
- Conference
- 2020 IEEE 17th International Symposium on Biomedical Imaging Workshops (ISBI Workshops) (Iowa City, IA, USA, 04/04/2020)
- Identifiers
- 991005543926107891
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Conference paper
Metrics
59 Record Views