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

Ing Tsung Hsiao, Anand Rangarajan, Gene Gindi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-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 languageEnglish
Title of host publication2002 IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Proceedings
PublisherIEEE Computer Society
Pages409-412
Number of pages4
ISBN (Electronic)078037584X
DOIs
StatePublished - 2002
EventIEEE International Symposium on Biomedical Imaging, ISBI 2002 - Washington, United States
Duration: 07 07 200210 07 2002

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2002-January
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Conference

ConferenceIEEE International Symposium on Biomedical Imaging, ISBI 2002
Country/TerritoryUnited States
CityWashington
Period07/07/0210/07/02

Bibliographical note

Publisher Copyright:
© 2002 IEEE.

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