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DOE OSTI · 22531413

Maximum Likelihood Expectation-Maximization Algorithms Applied to Localization and Identification of Radioactive Sources with Recent Coded Mask Gamma Cameras

Lemaire, H.·Barat, E.·Carrel, F.·Dautremer, T.·Dubos, S.·Limousin, O.·Montagu, T.·Normand, S.·Schoepff, V.·Amgarou, K.·Menaa, N.·Angelique, J. -C.·Patoz, A.
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Abstract

In this work, we tested Maximum likelihood expectation-maximization (MLEM) algorithms optimized for gamma imaging applications on two recent coded mask gamma cameras. We respectively took advantage of the characteristics of the GAMPIX and Caliste HD-based gamma cameras: noise reduction thanks to mask/anti-mask procedure but limited energy resolution for GAMPIX, high energy resolution for Caliste HD. One of our short-term perspectives is the test of MAPEM algorithms integrating specific prior values for the data to reconstruct adapted to the gamma imaging topic. (authors)

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46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY97 MATHEMATICS AND COMPUTINGALGORITHMSBIOMEDICAL RADIOGRAPHYENERGY RESOLUTIONGAMMA CAMERASMAXIMUM-LIKELIHOOD FITNOISERADIATION SOURCES

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Lemaire, H., Barat, E., Carrel, F., Dautremer, T., Dubos, S., Limousin, O., Montagu, T., Normand, S., Schoepff, V., Amgarou, K., Menaa, N., Angelique, J. -C., Patoz, A.. 2015-07-01. Maximum Likelihood Expectation-Maximization Algorithms Applied to Localization and Identification of Radioactive Sources with Recent Coded Mask Gamma Cameras. https://www.osti.gov/biblio/22531413

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