Keywords:
iterative image reconstruction, edge-enhancing denoising, non-linear filter, x-ray CT, fast algorithms
Iterative image reconstruction algorithms are commonly used to optimize an objective function, especially when the objective function is non-quadratic. Generally speaking, the iterative algorithms are computationally inefficient. This paper presents a fast algorithm that has one backprojection and no forward projection. This fast algorithm can be used to replace many iterative algorithms. This paper derives an ad hoc method to solve an optimization problem. The non-quadratic constraint, for example, an edge-preserving de-noising constraint is implemented as a non-linear filter. The algorithm is derived based on the POCS (projections onto projections onto convex sets) approach. A windowed FBP (filtered backprojection) algorithm enforces the data fidelity. An iterative procedure, divided into segments, enforces edge-enhancement denoising. Each segment performs non-linear filtering. The derived iterative algorithm is computationally efficient. It contains only one backprojection and no forward projection. Low-dose CT data are used for algorithm feasibility studies. The non-linearity is implemented as an edge-enhancing noise-smoothing filter. The proposed iterative algorithm is an ad hoc method. The patient studies results demonstrate its effectiveness in processing lowdose x-ray CT data.
- Gengsheng L. Zeng
- Weber State University, USA
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