- Gengsheng L Zeng: Department of Engineering, Weber State University, Ogden, Utah 84408 USA and with the Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, 84108, USA.
Due to noise, the iterative image reconstruction algorithms must stop early before reaching the convergence. There is an optimal stopping point, at which the discrepancy of the reconstruction to the true image reaches minimum. It is still an open problem to find this optimal stopping point. This paper establishes two approximate relationships towards solving this open problem. The first approximate relationship is between the iterative Landweber algorithm and an iteration-number-emulated filtered backprojection (FBP) algorithm. The second approximate relationship is between the optimal iteration-number-emulated FBP reconstruction and the optimal projection-domain filtered data. These two relationships can help us to estimate the optimal stopping point.