Reconstruction From Limited-Angle Projections Based on a Transformation

ABSTRACT Limited angle computed tomography (CT) is common in medical and industrial applications where incomplete projection data can cause artifacts in the reconstructed image. we propose a new algorithm for reconstructing a density function , (an image), in the plane from a limited number of Radon projections on a range of angles for some acute angle Assuming that is subjected to a linear transformation to produce a new image ; the new image is then recovered. In fact, the well-known relation between the desired image and the transformed image, in the transform domain, is used. This relation allows us to map a uniformly distributed view angles over to some range of view angles that are available for the original image. It is known that uniformizing the view angles of projections improves the performance of some algorithms such as the filter back projection algorithm. In this way, the transformed image is reconstructed from the uniformly distributed angles that correspond to a limited number of projections. The effectiveness of the proposed approach is validated by simulation and by applications to synthetic images.