Reconstruction method of differentiated backprojection-projection onto convex sets in the interior problem and design of bone-nail model

Abstract

This work focuses on the application of the reconstruction method of differentiated backprojection (DBP)-projection onto convex sets (POCS) in the interior problem. First, we present the definition of the interior problem and real truncated Hilbert transform, and then outline the implementation steps of DBP-POCS. After that, we introduce the middle-part known condition for region of interest (ROI) accurate reconstruction and the unique condition of the interior problem, and verify the uniqueness and stability of the interior problem accurate reconstruction through numerical experiments, and then compare the results for the interior problem in reconstruction images using filtered backprojection (FBP). In addition, the authors also design the application models of ROI reconstruction and make an initial attempt to the application of DBP-POCS method in the interior problem.