
Proceedings Paper
Accelerating ordered-subsets image reconstruction for x-ray CT using double surrogatesFormat | Member Price | Non-Member Price |
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Paper Abstract
Conventional ordered-subsets (OS) methods for regularized image reconstruction involve computing the gradient of the
regularizer for every subset update. When dealing with large problems with many subsets, such as in 3D X-ray CT, computing
the gradient for each subset update can be very computationally expensive. To mitigate this issue, some investigators
use unregularized iterations followed by a denoising operation after updating all subsets.1 Although such methods save
computation, their convergence properties are uncertain, and since they may not be minimizing any particular cost function
it becomes more difficult to design regularization parameters. Furthermore, it is known that inserting filtering steps into unregularized
algorithms can lead to undesirable spatial resolution properties.2 Our goal here is to reduce the computational
cost without inducing such problems. We propose a new OS-type algorithm that is derived using optimization transfer
principles. The proposed method allows the gradient of the regularizer to be updated less frequently, and thus reduces the
computational expense when many subsets are used. Our derivation leads to a correction term that accounts for the fact
that the regularizer gradient is updated less frequent than every sub-iteration. Simulations and a phantom experiment show
that the proposed method reconstructed images with compatible image quality within reduced computation time.
Paper Details
Date Published: 3 March 2012
PDF: 9 pages
Proc. SPIE 8313, Medical Imaging 2012: Physics of Medical Imaging, 83131X (3 March 2012); doi: 10.1117/12.911531
Published in SPIE Proceedings Vol. 8313:
Medical Imaging 2012: Physics of Medical Imaging
Norbert J. Pelc; Robert M. Nishikawa; Bruce R. Whiting, Editor(s)
PDF: 9 pages
Proc. SPIE 8313, Medical Imaging 2012: Physics of Medical Imaging, 83131X (3 March 2012); doi: 10.1117/12.911531
Show Author Affiliations
Jang Hwan Cho, Univ. of Michigan (United States)
Jeffrey A. Fessler, Univ. of Michigan (United States)
Published in SPIE Proceedings Vol. 8313:
Medical Imaging 2012: Physics of Medical Imaging
Norbert J. Pelc; Robert M. Nishikawa; Bruce R. Whiting, Editor(s)
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