A new convergent map reconstruction algorithm for emission tomography using ordered subsets and separable surrogates

Ing Tsung Hsiao; Anand Rangarajan; Gene Gindi

doi:10.1109/ISBI.2002.1029281

A new convergent map reconstruction algorithm for emission tomography using ordered subsets and separable surrogates

Ing Tsung Hsiao
, Anand Rangarajan
, Gene Gindi

Department of Medical Imaging and Radiological Sciences

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

31 Scopus citations

Abstract

We investigate a new, fast and provably convergent MAP reconstruction algorithm for emission tomography. The new algorithm, termed C-OSEM has its origin in the alternating algorithm derivation of the weil known EM algorithm for emission tomography. In this re-derivation, the complete data explicitly enters the objective function as an unknown variable. While the entire complete data gets updated in each iteration of EM, in C-OSEM the complete data is updated only along ordered subsets. C-OSEM has a straightforward extension to the MAP case especially when using convex, smoothing priors. Unlike RAMLA and BSREM, C-OSEM does not require relaxation parameters to be set at each iteration. We derive the MAP C-OSEM algorithm using the separable surrogate method and anecdotally compare performance with MAP EM and BSREM.

Original language	English
Title of host publication	2002 IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Proceedings
Publisher	IEEE Computer Society
Pages	409-412
Number of pages	4
ISBN (Electronic)	078037584X
DOIs	https://doi.org/10.1109/ISBI.2002.1029281
State	Published - 2002
Event	IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Washington, United States Duration: 07 07 2002 → 10 07 2002

Publication series

Name	Proceedings - International Symposium on Biomedical Imaging
Volume	2002-January
ISSN (Print)	1945-7928
ISSN (Electronic)	1945-8452

Conference

Conference	IEEE International Symposium on Biomedical Imaging, ISBI 2002
Country/Territory	United States
City	Washington
Period	07/07/02 → 10/07/02

Bibliographical note

Publisher Copyright:
© 2002 IEEE.

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10.1109/ISBI.2002.1029281

Cite this

Hsiao, I. T., Rangarajan, A., & Gindi, G. (2002). A new convergent map reconstruction algorithm for emission tomography using ordered subsets and separable surrogates. In 2002 IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Proceedings (pp. 409-412). Article 1029281 (Proceedings - International Symposium on Biomedical Imaging; Vol. 2002-January). IEEE Computer Society. https://doi.org/10.1109/ISBI.2002.1029281

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title = "A new convergent map reconstruction algorithm for emission tomography using ordered subsets and separable surrogates",

abstract = "We investigate a new, fast and provably convergent MAP reconstruction algorithm for emission tomography. The new algorithm, termed C-OSEM has its origin in the alternating algorithm derivation of the weil known EM algorithm for emission tomography. In this re-derivation, the complete data explicitly enters the objective function as an unknown variable. While the entire complete data gets updated in each iteration of EM, in C-OSEM the complete data is updated only along ordered subsets. C-OSEM has a straightforward extension to the MAP case especially when using convex, smoothing priors. Unlike RAMLA and BSREM, C-OSEM does not require relaxation parameters to be set at each iteration. We derive the MAP C-OSEM algorithm using the separable surrogate method and anecdotally compare performance with MAP EM and BSREM.",

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Hsiao, IT, Rangarajan, A & Gindi, G 2002, A new convergent map reconstruction algorithm for emission tomography using ordered subsets and separable surrogates. in 2002 IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Proceedings., 1029281, Proceedings - International Symposium on Biomedical Imaging, vol. 2002-January, IEEE Computer Society, pp. 409-412, IEEE International Symposium on Biomedical Imaging, ISBI 2002, Washington, United States, 07/07/02. https://doi.org/10.1109/ISBI.2002.1029281

A new convergent map reconstruction algorithm for emission tomography using ordered subsets and separable surrogates. / Hsiao, Ing Tsung; Rangarajan, Anand; Gindi, Gene.
2002 IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Proceedings. IEEE Computer Society, 2002. p. 409-412 1029281 (Proceedings - International Symposium on Biomedical Imaging; Vol. 2002-January).

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

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N2 - We investigate a new, fast and provably convergent MAP reconstruction algorithm for emission tomography. The new algorithm, termed C-OSEM has its origin in the alternating algorithm derivation of the weil known EM algorithm for emission tomography. In this re-derivation, the complete data explicitly enters the objective function as an unknown variable. While the entire complete data gets updated in each iteration of EM, in C-OSEM the complete data is updated only along ordered subsets. C-OSEM has a straightforward extension to the MAP case especially when using convex, smoothing priors. Unlike RAMLA and BSREM, C-OSEM does not require relaxation parameters to be set at each iteration. We derive the MAP C-OSEM algorithm using the separable surrogate method and anecdotally compare performance with MAP EM and BSREM.

AB - We investigate a new, fast and provably convergent MAP reconstruction algorithm for emission tomography. The new algorithm, termed C-OSEM has its origin in the alternating algorithm derivation of the weil known EM algorithm for emission tomography. In this re-derivation, the complete data explicitly enters the objective function as an unknown variable. While the entire complete data gets updated in each iteration of EM, in C-OSEM the complete data is updated only along ordered subsets. C-OSEM has a straightforward extension to the MAP case especially when using convex, smoothing priors. Unlike RAMLA and BSREM, C-OSEM does not require relaxation parameters to be set at each iteration. We derive the MAP C-OSEM algorithm using the separable surrogate method and anecdotally compare performance with MAP EM and BSREM.

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Hsiao IT, Rangarajan A, Gindi G. A new convergent map reconstruction algorithm for emission tomography using ordered subsets and separable surrogates. In 2002 IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Proceedings. IEEE Computer Society. 2002. p. 409-412. 1029281. (Proceedings - International Symposium on Biomedical Imaging). doi: 10.1109/ISBI.2002.1029281

A new convergent map reconstruction algorithm for emission tomography using ordered subsets and separable surrogates

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