Development of an Ideal Observer that Incorporates Nuisance Parameters and Processes List-Mode Data
Data Analysis, Statistics and Probability
2016-03-21 v1 Computer Vision and Pattern Recognition
Abstract
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.
Cite
@article{arxiv.1602.01449,
title = {Development of an Ideal Observer that Incorporates Nuisance Parameters and Processes List-Mode Data},
author = {Christopher J. MacGahan and Matthew A. Kupinski and Nathan R. Hilton and Erik M. Brubaker and William C. Johnson},
journal= {arXiv preprint arXiv:1602.01449},
year = {2016}
}