Detectability of anomalies from a few noisy tomographic projections
Abstract
The problem of detecting an anomaly from a limited number of noisy tomographic projections is addressed from the statistical point of view. An unknown two (or three)-dimensional scene is composed of a background, considered as a nuisance parameter, with a possibly hidden anomaly. A parametric approach is proposed to reduce the lack of a priori information and an optimal test is designed. To decide between two hypotheses (absence or presence of the anomaly), the statistical test eliminates the background, which can hide the anomaly. New results on anomaly detectability are proposed and discussed in this paper. It is shown that a size-limited anomaly is better detectable with several projections.