GPU-accelerated block matching algorithm for deformable registration of lung CT images

Min Li; Zhikang Xiang; Liang Xiao; Edward Castillo; Richard Castillo; Thomas Guerrero

doi:10.1109/PIC.2015.7489856

GPU-accelerated block matching algorithm for deformable registration of lung CT images

Min Li, Zhikang Xiang, Liang Xiao, Edward Castillo, Richard Castillo, Thomas Guerrero

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

Deformable registration (DR) is a key technology in the medical field. However, many of the existing DR methods are time-consuming and the registration accuracy needs to be improved, which prevents their clinical applications. In this study, we propose a parallel block matching algorithm for lung CT image registration, in which the sum of squared difference metric is modified as the cost function and the moving least squares approach is used to generate the full displacement field. The algorithm is implemented on Graphic Processing Unit (GPU) with the Compute Unified Device Architecture (CUDA). Results show that the proposed parallel block matching method achieves a fast runtime while maintaining an average registration error (standard deviation) of 1.08 (0.69) mm.

Original language	English (US)
Title of host publication	Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015
Editors	Liang Xiao, Yinglin Wang
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	292-295
Number of pages	4
ISBN (Electronic)	9781467380867
DOIs	https://doi.org/10.1109/PIC.2015.7489856
State	Published - Jun 10 2016
Externally published	Yes
Event	3rd IEEE International Conference on Progress in Informatics and Computing, PIC 2015 - Nanjing, China Duration: Dec 18 2015 → Dec 20 2015

Publication series

Name	Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015

Other

Other	3rd IEEE International Conference on Progress in Informatics and Computing, PIC 2015
Country/Territory	China
City	Nanjing
Period	12/18/15 → 12/20/15

Keywords

Deformable registration
Graphic Processing Unit
block matching

ASJC Scopus subject areas

Computer Science Applications
Computer Vision and Pattern Recognition
Information Systems

Access to Document

10.1109/PIC.2015.7489856

Cite this

Li, M., Xiang, Z., Xiao, L., Castillo, E., Castillo, R., & Guerrero, T. (2016). GPU-accelerated block matching algorithm for deformable registration of lung CT images. In L. Xiao, & Y. Wang (Eds.), Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015 (pp. 292-295). Article 7489856 (Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PIC.2015.7489856

GPU-accelerated block matching algorithm for deformable registration of lung CT images. / Li, Min; Xiang, Zhikang; Xiao, Liang et al.
Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015. ed. / Liang Xiao; Yinglin Wang. Institute of Electrical and Electronics Engineers Inc., 2016. p. 292-295 7489856 (Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Li, M, Xiang, Z, Xiao, L, Castillo, E, Castillo, R & Guerrero, T 2016, GPU-accelerated block matching algorithm for deformable registration of lung CT images. in L Xiao & Y Wang (eds), Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015., 7489856, Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015, Institute of Electrical and Electronics Engineers Inc., pp. 292-295, 3rd IEEE International Conference on Progress in Informatics and Computing, PIC 2015, Nanjing, China, 12/18/15. https://doi.org/10.1109/PIC.2015.7489856

Li M, Xiang Z, Xiao L, Castillo E, Castillo R, Guerrero T. GPU-accelerated block matching algorithm for deformable registration of lung CT images. In Xiao L, Wang Y, editors, Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015. Institute of Electrical and Electronics Engineers Inc. 2016. p. 292-295. 7489856. (Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015). doi: 10.1109/PIC.2015.7489856

Li, Min ; Xiang, Zhikang ; Xiao, Liang et al. / GPU-accelerated block matching algorithm for deformable registration of lung CT images. Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015. editor / Liang Xiao ; Yinglin Wang. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 292-295 (Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015).

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abstract = "Deformable registration (DR) is a key technology in the medical field. However, many of the existing DR methods are time-consuming and the registration accuracy needs to be improved, which prevents their clinical applications. In this study, we propose a parallel block matching algorithm for lung CT image registration, in which the sum of squared difference metric is modified as the cost function and the moving least squares approach is used to generate the full displacement field. The algorithm is implemented on Graphic Processing Unit (GPU) with the Compute Unified Device Architecture (CUDA). Results show that the proposed parallel block matching method achieves a fast runtime while maintaining an average registration error (standard deviation) of 1.08 (0.69) mm.",

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AU - Guerrero, Thomas

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AB - Deformable registration (DR) is a key technology in the medical field. However, many of the existing DR methods are time-consuming and the registration accuracy needs to be improved, which prevents their clinical applications. In this study, we propose a parallel block matching algorithm for lung CT image registration, in which the sum of squared difference metric is modified as the cost function and the moving least squares approach is used to generate the full displacement field. The algorithm is implemented on Graphic Processing Unit (GPU) with the Compute Unified Device Architecture (CUDA). Results show that the proposed parallel block matching method achieves a fast runtime while maintaining an average registration error (standard deviation) of 1.08 (0.69) mm.

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GPU-accelerated block matching algorithm for deformable registration of lung CT images

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Keywords

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