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Development of an ideal Observer that incorporates nuisance parameters and processes list-mode data

Journal of the Optical Society of America A: Optics and Image Science, and Vision

MacGahan, Christopher J.; Kupinski, Matthew A.; Hilton, Nathan R.; Brubaker, Erik B.; Johnson, William C.

Observer models were developed to process data in list-mode format in order to perform binary discrimination tasks for use in an arms-control-treaty context. Data used in this study was generated using GEANT4 Monte Carlo simulations for photons using custom models of plutonium inspection objects and a radiation imaging system. Observer model performance was evaluated and presented using the area under the receiver operating characteristic curve. The ideal observer was studied under both signal-known-exactly conditions and in the presence of unknowns such as object orientation and absolute count-rate variability; when these additional sources of randomness were present, their incorporation into the observer yielded superior performance.

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Optimal imaging for treaty verification FY2014 annual report

Hilton, Nathan R.; Kupinski, Matthew A.; MacGahan, Christopher J.; Johnson, William C.; Brubaker, Erik B.

FY2014 technical report of our project funded by DNN R&D that leverages advanced inference methods developed for medical and adaptive imaging to address arms control applications. We seek a method to acquire and analyze imaging data of declared treaty-accountable items without creating an image of those objects or otherwise storing or revealing any classified information. Such a method would avoid the use of classified-information barriers. We present our progress on FY2014 tasks defined in our life-cycle plan. We also describe some future work that is part of the continuation of this project in FY2015 and beyond as part of a venture that joins ours with a related PNNL project.

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17 Results
17 Results