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GPU-based streaming architectures for fast cone-beam CT image reconstruction and demons deformable registration.
Phys Med Biol. 2007 Oct 07; 52(19):5771-83.PM

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.

Authors+Show Affiliations

Sharp GC
Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA 02114, USA.
Kandasamy N
No affiliation info available
Singh H
No affiliation info available
Folkert M
No affiliation info available

MeSH

AlgorithmsPhantoms, ImagingRadiographic Image EnhancementRadiographic Image Interpretation, Computer-AssistedReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueTomography, Spiral Computed

Pub Type(s)

Evaluation Study
Journal Article

Language

eng

PubMed ID

17881799

Citation

Sharp, G C., et al. "GPU-based Streaming Architectures for Fast Cone-beam CT Image Reconstruction and Demons Deformable Registration." Physics in Medicine and Biology, vol. 52, no. 19, 2007, pp. 5771-83.
Sharp GC, Kandasamy N, Singh H, et al. GPU-based streaming architectures for fast cone-beam CT image reconstruction and demons deformable registration. Phys Med Biol. 2007;52(19):5771-83.
Sharp, G. C., Kandasamy, N., Singh, H., & Folkert, M. (2007). GPU-based streaming architectures for fast cone-beam CT image reconstruction and demons deformable registration. Physics in Medicine and Biology, 52(19), 5771-83.
Sharp GC, et al. GPU-based Streaming Architectures for Fast Cone-beam CT Image Reconstruction and Demons Deformable Registration. Phys Med Biol. 2007 Oct 7;52(19):5771-83. PubMed PMID: 17881799.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - GPU-based streaming architectures for fast cone-beam CT image reconstruction and demons deformable registration. AU - Sharp,G C, AU - Kandasamy,N, AU - Singh,H, AU - Folkert,M, Y1 - 2007/09/10/ PY - 2007/9/21/pubmed PY - 2007/12/6/medline PY - 2007/9/21/entrez SP - 5771 EP - 83 JF - Physics in medicine and biology JO - Phys Med Biol VL - 52 IS - 19 N2 - 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. SN - 0031-9155 UR - https://www.unboundmedicine.com/medline/citation/17881799/GPU_based_streaming_architectures_for_fast_cone_beam_CT_image_reconstruction_and_demons_deformable_registration_ DB - PRIME DP - Unbound Medicine ER -