Relaxed Ordered Subsets Algorithm for Image Restoration of Confocal Microscopy
dc.contributor.author | Sotthivirat, Saowapak | en_US |
dc.contributor.author | Fessler, Jeffrey A. | en_US |
dc.date.accessioned | 2011-08-18T18:20:58Z | |
dc.date.available | 2011-08-18T18:20:58Z | |
dc.date.issued | 2002-11-07 | en_US |
dc.identifier.citation | Sotthivirat, S.; Fessler, J.A. (2002). "Relaxed Ordered Subsets Algorithm for Image Restoration of Confocal Microscopy." International Symposium on Biomedical Imaging: 1051-1054. <http://hdl.handle.net/2027.42/85875> | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/85875 | |
dc.description.abstract | The expectation-maximization (EM) algorithm for maximum-likelihood image recovery converges very slowly. Thus, the ordered subsets EM (OS-EM) algorithm has been widely used in image reconstruction for tomography due to an order-of-magnitude acceleration over the EM algorithm. However, OS-EM is not guaranteed to converge. The recently proposed ordered subsets, separable paraboloidal surrogates (OS-SPS) algorithm with relaxation has been shown to converge to the optimal point while providing fast convergence. In this paper, we develop a relaxed OS-SPS algorithm for image restoration. Because data acquisition is different in image restoration than in tomography, we adapt a different strategy for choosing subsets in image restoration which uses pixel location rather than projection angles. Simulation results show that the order-of-magnitude acceleration of the relaxed OS-SPS algorithm can be achieved in restoration. Thus the speed and the guarantee of the convergence of the OS algorithm is advantageous for image restoration as well. | en_US |
dc.publisher | IEEE | en_US |
dc.title | Relaxed Ordered Subsets Algorithm for Image Restoration of Confocal Microscopy | en_US |
dc.type | article | en_US |
dc.subject.hlbsecondlevel | Biomedical Engineering | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Dept. of Electrical Engineering and Computer Science. | en_US |
dc.identifier.pmid | 18244633 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/85875/1/Fessler174.pdf | |
dc.identifier.doi | 10.1109/ISBI.2002.1029445 | en_US |
dc.identifier.source | International Symposium on Biomedical Imaging | en_US |
dc.owningcollname | Electrical Engineering and Computer Science, Department of (EECS) |
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