NDLI: GPU implementation of list-mode DRAMA for real-time OpenPET image reconstruction

Content Provider	IEEE Xplore Digital Library
Author	Kinouchi, S. Yamaya, T. Yoshida, E. Tashima, H. Kudo, H. Suga, M.
Copyright Year	2010
Description	Author affiliation: National Institute of Radiological Sciences, Japan (Yamaya, T.; Yoshida, E.; Tashima, H.) \|\| Graduate School of Engineering, Chiba University, Japan (Kinouchi, S.; Suga, M.) \|\| Graduate School of Systems and Information Engineering, University of Tsukuba, Japan (Kudo, H.)
Abstract	The OpenPET, which has a physically opened space between two detector rings, is our new geometry to enable PET imaging during radiation therapy. Especially, tracking a moving target such as a tumor in the lung will become possible if the real-time imaging system is realized. In this paper, we developed a list-mode image reconstruction method using general-purpose computing on graphics processing units (GPGPUs) toward real-time image reconstruction. We used the dynamic row-action maximum likelihood algorithm (DRAMA). For GPU implementation, efficiency of acceleration depends on implementation methods; reduced conditional statements and efficient memory accesses are required. On the other hand, accurate system model is required to improve quality of reconstructed images. Therefore, we developed a new system model which was suited for the GPU implementation. In the new system model, the detector response functions (DRFs), which were calculated analytically to represent the probability distribution of each LOR, were modeled by sixth-order polynomial functions. The system model enabled us to calculate each element of the system matrix with reduced conditional statements. We applied the developed method to a small OpenPET prototype, which was developed for a proof-of-concept. We compared the proposed system model to the sub-LOR model, a geometrically-defined accurate system model which we had previously proposed. The difference between the reconstructed images with the new system model using GPU and the sub-LOR model using CPU was very small. Our new system model on GPU was 46.3 times faster than the sub-LOR model on CPU.
Starting Page	2273
Ending Page	2276
File Size	638918
Page Count	4
File Format	PDF
ISBN	9781424491063
ISSN	10957863
e-ISBN	9781424491056
DOI	10.1109/NSSMIC.2010.5874188
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Graphics processing unit Image reconstruction Real time systems Prototypes Positron emission tomography Detectors OpenPET List-mode reconstruction GPU
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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