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A Volumetric Method for Quantification of Cerebral Vasospasm in a Murine Model of Subarachnoid Hemorrhage
Published on: July 28, 2018
Skeletonization of volumetric angiograms for display
1Department of Electrical and Computer Engineering and Center for Interlligent Machine, McGill University, 3480 University Street, Montreal, Que Canada H3A 2A7. yidingr@cim.mcgill.ca
Summary
This study presents an efficient method for extracting quantitative shape features from 3D angiograms using vessel centerline skeletons. The approach ensures accurate geometric analysis for improved visualization and understanding of vascular structures.
Area of Science:
- Medical Imaging
- Computer Vision
- Computational Geometry
Background:
- Accurate quantitative shape features of 3D angiograms are crucial for medical diagnosis and analysis.
- Existing methods may struggle with preserving connectivity, topology, and geometric constraints during skeletonization.
Purpose of the Study:
- To develop an efficient and robust method for extracting quantitative shape features from 3D angiograms.
- To obtain a curve-like skeleton representation that preserves connectivity and topology while satisfying geometric constraints.
Main Methods:
- Utilized a voxel coding approach to generate connected, unit-thick paths representing vessel centerlines.
- Applied a moving average filter for skeleton smoothing to estimate features like tangent and curvature.
- Ensured complete representation of the original object without omissions.
Main Results:
- Developed an efficient method for identifying shape components in 3D angiograms.
- Achieved linear computational cost, proportional to the number of object voxels (N(object)).
- Demonstrated robustness of the method against boundary noise in volumetric data.
Conclusions:
- The proposed method enables accurate estimation of vessel length, orientation, curvature, and torsion from 3D angiograms.
- This technique enhances the quantitative analysis and display of vascular structures.
- The method is computationally efficient and reliable for medical imaging applications.
