The University of Arizona
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X-ray measurement model and information-theoretic metric incorporating material variations with energy and spatial correlations

Sparsity in Imaging

X-ray measurement model and information-theoretic metric incorporating material variations with energy and spatial correlations
Series: Sparsity in Imaging
Location: Department of Electrical & Computer Engineering ECE 530
Presenter: Yijun Ding, College of Opical Sciences, UofA

A task-specific assessment of the performance of an imaging system requires knowledge of the statistical properties of the forward model and the objects. The task-specific performance of X-ray systems is ultimately limited by the shot noise of the X-ray photons, the inherent variations in the material composition and the uncertainties in the imaging system itself. Extending our prior work, we propose a multi-energy X-ray measurement model incorporating material variability with energy and spatial correlations. Based on this measurement model, we provide analytical expressions for bounds on the probability of error (Pe) to quantify the performance limits of an X-ray measurement system for binary classification task.

 

 

(Please note the venue: ECE 530)