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          Institute: MPI für biologische Kybernetik     Collection: Biologische Kybernetik     Display Documents



ID: 461824.0, MPI für biologische Kybernetik / Biologische Kybernetik
A new non-monotonic algorithm for PET image reconstruction
Authors:Sra, S.; Kim, D.; Dhillon, I.; Schölkopf, B.
Editors:Yu, B.
Date of Publication (YYYY-MM-DD):2009-10
Title of Proceedings:Proceedings of the IEEE Nuclear Science Symposium Conference Record (NSS/MIC 2009)
Start Page:2500
End Page:2502
Physical Description:3
Audience:Not Specified
Intended Educational Use:No
Abstract / Description:Maximizing some form of Poisson likelihood (either with or without penalization) is central to image reconstruction algorithms in emission tomography. In this paper we introduce NMML, a non-monotonic algorithm for maximum likelihood PET image reconstruction. NMML offers a simple and flexible procedure that also easily incorporates standard convex regular-ization for doing penalized likelihood estimation. A vast number image reconstruction algorithms have been developed for PET, and new ones continue to be designed. Among these, methods based on the expectation maximization (EM) and ordered-subsets (OS) framework seem to have enjoyed the greatest popularity. Our method NMML differs fundamentally from methods based on EM: i) it does not depend on the concept of optimization transfer (or surrogate functions); and ii) it is a rapidly converging nonmonotonic descent procedure. The greatest strengths of NMML, however, are its simplicity, efficiency, and scalability, which make it especially attractive for tomograph
ic reconstruction. We provide a theoretical analysis NMML, and empirically observe it to outperform standard EM based methods, sometimes by orders of magnitude. NMML seamlessly allows integreation of penalties (regularizers) in the likelihood. This ability can prove to be crucial, especially because with the rapidly rising importance of combined PET/MR scanners, one will want to include more “prior” knowledge into the reconstruction.
External Publication Status:published
Document Type:Conference-Paper
Communicated by:Holger Fischer
Affiliations:MPI für biologische Kybernetik/Empirical Inference (Dept. Schölkopf)
Identifiers:LOCALID:5958
URL:http://www.nss-mic.org/2009/NSSMain.asp
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