| Computed tomography (CT) is a technique for imaging cross-sections of an object using a series of X-ray measurements. It has been widely applied in diagnostic medicine and industrial non-destructive testing. Computed Tomography is one of the advanced means for non-destructive testing (NDT), which has the virtues of non-destructive, non-contact and high resolution. It is called the best means for NDT by the circle of international NDT. With the wide application of CT, reconstruction algorithm has become the focus of many studies.The researches in this paper fall into two parts: Cone-beam CT projections rebinning algorithm and expectation maximization algorithm. In terms of Cone-beam CT projections rebinning algorithm, first, based on traditional FDK algorithm and rebinning theory, the reconstruction formula of projections rebinning algorithm is obtained. Then the projection data are rebinned to oblique parallel projection data. The rebinned oblique parallel projection data are preweighting filtered. Finally, the filtered projection data are backprojected to the final reconstructed image data. This method describes a new idea for Cone-beam CT reconstruction. Though its image quality has no obvious improvement than FDK algorithm, it is the basis of many helix CT reconstruction algorithms. In terms of EM algorithm, according to projection geometry model and EM theory, the likelihood function is obtained and the EM algorithm is applied to XCT. Several improved EM algorithms such as MAP-EM, OS-EM, OR-EM are also implemented in this section. With the study and analysis of these algorithms, the shortcoming of MAP-EM is noted, this algorithm yields one step late because it uses the data of last iteration. Then an improved MAP-EM iterative algorithm is proposed. The improved algorithm solved above problem. So it can yield better reconstruction than MAP-EM. At the same time its convergence is faster. Experimental results show the improved algorithm can suppress noise effectively. |
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