NDLI: Stochastic image reconstruction method for Compton camera

Content Provider	IEEE Xplore Digital Library
Author	Andreyev, A. Sitek, A. Celler, A.
Copyright Year	2009
Description	Author affiliation: Department of Radiology, University of British Columbia, Vancouver, Canada (Andreyev, A.; Celler, A.) \|\| Department of Radiology, Harvard Medical School and Brigham and Women's Hospital, Boston, USA (Sitek, A.)
Abstract	Compton camera has been proposed as an imaging tool in astronomy, industry, homeland security and medical imaging where source location can be identified based on detection of Compton scattered and photoabsorbed photons. However, due to the geometrical complexity of the problem, image reconstruction from Compton camera data is difficult and/or ineffective when using techniques such as filtered backprojection (FBP) or maximum likelihood expectation maximization (MLEM). In this paper, we propose a novel stochastic origin ensembles (SOE) approach based on Markov chains (previously implemented and tested for PET) to the reconstruction of Compton camera data. The advantages of this method are that it is universal (i.e. works with any camera geometry), does not require any rebinning of acquired data, parallelizable, and does not require forward- and back-projection operations nor voxelization of the image space. During image reconstruction the origins of every measured events are the randomly assigned locations on the conical surface (which is the Compton camera analog of lines-of-response in PET). Therefore, the image is defined as an event ensemble holding the coordinates of all possible event origins. During the course of the reconstruction, origins of the events are randomly moved and the acceptance of the new event origin is determined by the acceptance probability, which is proportional to the change in event density. For example, if event density at the new location is higher than in the previous location, the new position is always accepted. As a result of many iterations, the reconstructed image converges to the quasi-stationary state which can be voxelized and displayed. Comparison to the list-mode MLEM shows that SOE algorithm has similar performance in terms of image quality while clearly outperforming it in terms of reconstruction time. Implementation of corrections for detector energy resolution can be done at almost no additional computational cost, which is a major advantage of SOE over other reconstruction methods.
Starting Page	2985
Ending Page	2988
File Size	374233
Page Count	4
File Format	PDF
ISBN	9781424439614
ISSN	10957863
DOI	10.1109/NSSMIC.2009.5401592
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stochastic processes Image reconstruction Cameras Positron emission tomography Astronomy Terrorism Biomedical imaging Position measurement Electromagnetic scattering Particle scattering stochastic iterative reconstruction Compton camera image reconstruction listmode MLEM
Content Type	Text
Resource Type	Article

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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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