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A framework for the automatic generation of surface topologies for abdominal aortic aneurysm models
Judy Shum1, Amber Xu, Itthi Chatnuntawech
1Biomedical Engineering Department, Carnegie Mellon University, Pittsburgh, PA 15213-3890, USA.
Annals of Biomedical Engineering
|September 21, 2010
Summary
This study presents an algorithm to refine 3D models of abdominal aortic aneurysms (AAAs). The method improves surface quality for better analysis of AAA wall curvature changes.
Area of Science:
- Biomedical Engineering
- Medical Imaging Analysis
- Computational Geometry
Background:
- Patient-specific abdominal aortic aneurysms (AAAs) exhibit local curvature changes impacting risk assessment.
- Current 3D surface reconstruction from medical images often results in low-quality topologies with irregularities.
- Accurate geometric characterization is crucial for understanding AAA progression and rupture risk.
Purpose of the Study:
- To develop and validate an iterative algorithm for optimizing the quality of 3D surface topologies of abdominal aortic aneurysms (AAAs).
- To enable precise characterization of local curvature changes on the AAA outer wall surface.
- To provide a robust method for generating high-quality triangular surface meshes from segmented AAA masks.
Main Methods:
- An iterative algorithm combining geometry interpolation, topology refinement, and surface smoothing was developed.
- Delaunay triangulation adapted for AAA segmented masks was used to generate triangular surface topologies.
- A signed distance function represented the AAA wall boundary before triangulation.
- Node equilibrium and low-pass filtering were employed for mesh refinement and smoothing.
- Optimization of iterations was guided by element quality index and minimal AAA sac volume change.
Main Results:
- The algorithm automatically generates high-quality triangular surface topologies from segmented AAA data.
- Surface irregularities, sharp corners, and low-quality elements were significantly minimized.
- The refined topologies accurately represent the AAA outer wall geometry.
- The process ensures minimal change in AAA sac volume during refinement.
Conclusions:
- The developed framework successfully produces optimized, high-quality 3D surface meshes of patient-specific abdominal aortic aneurysms (AAAs).
- This method facilitates accurate characterization of local curvature changes, essential for clinical risk assessment.
- The automated approach enhances the reliability and efficiency of AAA geometric analysis.
