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Deformable meshes with automated topology changes for coarse-to-fine three-dimensional surface extraction
1Equipe INFODIS, laboratoire TIMC-IMAG, UMR CNRS 5525, Institut Albert Bonniot, Domaine de la Merci, La Tronche, France. Jacques-Olivier.Lachaud@imag.fr
Medical Image Analysis
|March 11, 2000
Summary
This study introduces a deformable model for object extraction from volumetric data. It efficiently recovers complex shapes using a coarse-to-fine strategy and dynamic topology adaptation.
Area of Science:
- Computer Vision
- Medical Image Analysis
- Geometric Modeling
Background:
- Extracting objects from volumetric data is challenging.
- Existing methods struggle with complex shapes and computational efficiency.
Purpose of the Study:
- To present a generic deformable model for robust object extraction.
- To enable efficient shape recovery of complex structures in volumetric data.
Main Methods:
- A dynamic triangulated surface model adapts geometry based on constraints.
- A novel framework allows for dynamic topology changes.
- A pyramid construction algorithm accelerates processing via multi-resolution images.
Main Results:
- The model successfully recovers shapes by altering geometry and topology.
- The coarse-to-fine approach with image pyramids significantly speeds up shape estimation.
- Complex objects with intricate geometries are accurately extracted.
Conclusions:
- The proposed deformable model offers a versatile solution for volumetric object extraction.
- The method enhances efficiency and accuracy for complex shape recovery.
- This approach has potential applications in various fields requiring volumetric data analysis.