A new tomography model for almost optimal detection of anomalies

In this paper a new methodology for detecting anomaly from few tomography projections is presented. This methodology exploits a statistical model adapted to the content of radiographs together with hypothesis testing theory. The main contributions are the following. First, using a generic model of the tomography acquisition pipeline, the whole non-destructive testing process is entirely automated. Second, by using testing theory the statistical properties of the proposed test are analytically established. This particularly permits the guaranteeing of a prescribed false-alarm probability and allows us to show that the proposed test is almost optimal. Experimental results show the sharpness of the established results and the relevance of the methodology.