Efficient solving algorithm for determining the exact sampling condition of limited-angle computed tomography reconstruction.

Efficient solving algorithm for determining the exact sampling condition of limited-angle computed tomography reconstruction. J Xray Sci Technol. 2019 Mar 07;: Authors: Li Z, Wang L, Zhang W, Cai A, Li L, Liang N, Yan B Abstract Total variation (TV) regularization-based iterative reconstruction algorithms have an impressive potential to solve limited-angle computed tomography with insufficient sampling projections. The analysis of exact reconstruction sampling conditions for a TV-minimization reconstruction model can determine the minimum number of scanning angle and minimize the scanning range. However, the large-scale matrix operations caused by increased testing phantom size is the computation bottleneck in determining the exact reconstruction sampling conditions in practice. When the size of the testing phantom increases to a certain scale, it is very difficult to analyze quantitatively the exact reconstruction sampling condition using existing methods. In this paper, we propose a fast and efficient algorithm to determine the exact reconstruction sampling condition for large phantoms. Specifically, the sampling condition of a TV minimization model is modeled as a convex optimization problem, which is derived from the sufficient and necessary condition of solution uniqueness for the L1 minimization model. An effective alternating direction minimization algorithm is developed to optimize the objective function by alternatively solv...
Source: Journal of X-Ray Science and Technology - Category: Radiology Tags: J Xray Sci Technol Source Type: research