Journal article
GPU-based streaming architectures for fast cone-beam CT image reconstruction and demons deformable registration
Physics in medicine & biology, v 52(19), pp 5771-5783
07 Oct 2007
PMID: 17881799
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This paper shows how to significantly accelerate cone-beam CT reconstruction and 3D deformable image registration using the stream-processing model. We describe data-parallel designs for the Feldkamp, Davis and Kress (FDK) reconstruction algorithm, and the demons deformable registration algorithm, suitable for use on a commodity graphics processing unit. The streaming versions of these algorithms are implemented using the Brook programming environment and executed on an NVidia 8800 GPU. Performance results using CT data of a preserved swine lung indicate that the GPU-based implementations of the FDK and demons algorithms achieve a substantial speedup--up to 80 times for FDK and 70 times for demons when compared to an optimized reference implementation on a 2.8 GHz Intel processor. In addition, the accuracy of the GPU-based implementations was found to be excellent. Compared with CPU-based implementations, the RMS differences were less than 0.1 Hounsfield unit for reconstruction and less than 0.1 mm for deformable registration.
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Details
- Title
- GPU-based streaming architectures for fast cone-beam CT image reconstruction and demons deformable registration
- Creators
- G C Sharp - Harvard UniversityN Kandasamy - Drexel UniversityH Singh - Drexel UniversityM Folkert - Harvard University
- Publication Details
- Physics in medicine & biology, v 52(19), pp 5771-5783
- Publisher
- Institute of Physics (IOP)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000250443200003
- Scopus ID
- 2-s2.0-34748901307
- Other Identifier
- 991019167911904721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Engineering, Biomedical
- Radiology, Nuclear Medicine & Medical Imaging