Statistical and physical content of low-energy photons in holospectral imaging.

Abstract

The utility of low-energy photons can be investigated using statistical and physical models. Holospectral imaging exploits the correlation between energy frames to optimize primary photon representation. A relationship between energy frames can be established by the physical description of low-energy photons (or events). It is shown that those events not only build an image with fortuitous correlation with the on-peak image but, in some cases, they are spatially indistinguishable from primary photons. Similarly, it is possible to show that an important proportion of the events detected at the primary energy are in fact distributed in more than one pixel and, consequently, are misplaced and should be rejected from the imaging process. The authors introduce the rationale for statistical and physical approaches and explain the various categories of photons considered in this study. Monte Carlo simulations were used to establish the rate of occurrence of each photon path.