A 2D multiresolution image reconstruction method in X-ray computed tomography.

We propose a multiresolution X-ray imaging method designed for non-destructive testing/evaluation (NDT/NDE) applications which can also be used for small animal imaging studies. Two sets of projections taken at different magnifications are combined and a multiresolution image is reconstructed. A geometrical relation is introduced in order to combine properly the two sets of data and the processing using wavelet transforms is described. The accuracy of the reconstruction procedure is verified through a comparison to the standard filtered backprojection (FBP) algorithm on simulated data.

Spatiotemporal decomposition in object-space along reconstruction in emission tomography.

Emission tomography has provided a new insight in brain mechanisms past years. Although reconstructions are nowadays mostly static, trend is going toward dynamic acquisitions and reconstructions. This opens a new range of investigations, for instance for drugs discovery. Indeed new drugs are studied through the dynamic ability of tissues to catch them. However, it is required to know radiotracer concentration of blood that irrigates tissues in order to draw conclusions on potentials of these drugs. This concentration is called 'input function' and this paper presents a new method for measuring it in a non-invasive way. Our new method relies on simultaneous estimations of vessels kinetics and vessels spatial distribution. These estimations are performed during the reconstruction process and take into account the statistical nature of measured signals. Indeed, this method is based on the maximisation of the likelihood of counts in detectors. It takes advantages of a non-negative matrix factorisation which separate spatial and temporal components. Results are very promising, since it estimates arterial input function accurately although object emits just a limited amount of photons, especially within the first minutes.