A collection for local inverse and CT image reconstruction

A collection for local inverse and CT image reconstructionThe local tomography does not need iteration and extrapolation. Unlike local tomography the algorithm of local inverse is an iterative algorithm with extrapolation. In the first paper the concept of local inverse is introduced; it is utilized to reconstruct the CT(computer tomography) image from truncated projections. In the second paper the local inverse is utilized to solve image reconstruction with untruncated projections. Iteration and

The local tomography does not need iteration and extrapolation. Unlike local tomography the algorithm of local inverse is an iterative algorithm with extrapolation. In the first paper the concept of local inverse is introduced; it is utilized to reconstruct the CT(computer tomography) image from truncated projections. In the second paper the local inverse is utilized to solve image reconstruction with untruncated projections. Iteration and reconstruction in sub-regions are utilized. This iterative algorithm can remarkably reduce artifacts of the reconstructed image. The third paper gives a general discussion about local inverse and an example differing from CT image reconstruction is given. The following discuss image reconstruction with general Hankel transform using fan beam projections, the generalized central slice theorem, E-M method for SPECT image reconstruction, Monte Carlo simulation for PET projections, one dimensional coded source and the constrained least squares estimation for image restoration.