Tomographic reconstruction from fewer projections

Abstract

In this paper, we present an innovative analytic algorithm for tomographic reconstruction from fewer numbers of projections. Back-projection has been customized to make it work even when the projections are not uniformly distributed, and (or) are missing at certain orientation(s). Contour information of the object has been used efficiently to ignore all points/pixels that lie outside the objects boundary. Aiming successful reconstruction with minimum number of projections an innovative interpolation methodology has been proposed to figure out all the missing projections. Based on the experiments on simulated and real medical images it has been shown that the proposed modality is capable of producing better reconstruction than the state-of-the-art methods with comparatively less number of projections.