A thresholding based iterative reconstruction method for limited-angle tomography data

Abstract

Limited-angle computed tomography is often imposed by in-situ experiments combining tomography with sample environments. The missing projection data causes artifacts in the tomographic reconstruction. We demonstrate that the correction of these numerical artifacts can be achieved by restoring the missing projections using an iterative reconstruction scheme. The reconstruction is regularized using segmentation, and thresholds determined from the histogram of reconstructed gray levels. The missing projections are simulated by forward projection and incorporated into the original measured dataset to give a complete angular span. This scheme typically converges within a few iterations. Results are presented for several measurements using parallel-beam synchrotron X-ray tomography and 165 degrees of valid projection data. A simple numerical simulation is used to verify the validity of the experimental results.