A VTK-based, CUDA-optimized Non-Parametric Vessel Detection Method
Yale University
| Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/3146 |
Published in The VTK Journal - 2010 January - December Submissions.
Submitted by Alark Joshi on 01-25-2010.
We present a VTK-based implementation of our non-parametric vessel detection method that identifies vascular structures using a polar neighborhood profile. To accelerate the computationally intensive parts of the algorithm, we leverage the hardware capabilities in commodity graphics hardware using Compute Unified Device Architecture (CUDA). We present the results of our performance analysis and provide source code and examples to validate the reproducibility of our results.
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| Paper Id: | 710 |
| Categories: | Feature extraction, Neighborhood filters |
| Keywords: | vessel detection, hardware acceleration, polar profile, CUDA, |
| Toolkit: | CMake, VTK |
| Revision: | 1 (01-25-2010) |
| Status: | Open for public review |
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| Full download: | .zip |
| Paper: | view, .pdf |
| Source code : | Download |
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