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PDFOpen Access (License Unspecified), Open Access
Thesis
GPU-accelerated deformable registration of cone-beam CT images: design and implementation in the compute unified device architecture
Master of Science (M.S.), Drexel University
Jul 2008
DOI:
https://doi.org/10.17918/etd-2865
Abstract
This thesis describes a stream-processing model for the demons deformable registration algorithm, suitable for use on a graphics processing unit (GPU). The streaming version of the demons algorithm is developed using the Compute Unified Device Architecture (CUDA) and executed on NVidia's 8800 GTS GPU. Performance results using cone-beam CT data of a preserved swine lung indicate that the GPU-based implementation achieves a substantial speedup of 60 times when compared to an optimized reference implementation on a 2.8 GHz Intel processor. In addition, the accuracy of the GPU-based implementation was found to be excellent, with an RMS difference of less than 0.1 mm when compared with the reference implementation.
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Details
- Title
- GPU-accelerated deformable registration of cone-beam CT images
- Creators
- Nakul Jain - DU
- Contributors
- Nagarajan Kandasamy (Advisor) - Drexel University (1970-)
- Awarding Institution
- Drexel University
- Degree Awarded
- Master of Science (M.S.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Resource Type
- Thesis
- Language
- English
- Academic Unit
- College of Engineering (1970-2026); Electrical (and Computer) Engineering [Historical]; Drexel University
- Other Identifier
- 2865; 991014632230404721