The Study Of Incomplete Projection Data CT Reconstruction

Computed tomography (CT) is a technique for imaging cross-sections of an object using a series of X-ray measurements in different views. It has been widely applied in diagnostic medicine and industrial non-destructive testing. However, sufficient projections can't be always obtained in practical applications. In the view of this point, the study of CT image reconstruction with incomplete projection data has great value of application. In this paper, local tomography algorithm with incomplete projection data and reconstruction algorithm from limited-angle are mainly studied.Local tomography is also called the reconstruction of region of interest (ROI). In this paper a local tomography algorithm based on wavelet is introduced. The algorithm makes use of the projection data of ROI to predict the surrounding data, and then obtains the reconstruction result with a local tomography algorithm based on wavelet. Experiment results show that the proposed algorithm could reduce the amount of the projection data used for reconstructing ROI, and obtain the reconstruction images with high quality.In practical applications of tomographic imaging, insufficient data reconstruction using a few projections from limited-angle is very important, for it will enable rapid scanning with a reduced x-ray dose delivered to the patient. In this paper, two different reconstruction algorithms from limited-angle are proposed. Firstly, a modified Tikhonov regularization CT image reconstruction algorithm from limited-angle is proposed. The modified Tikhonov regularization method adopts homotopy mapping to adjust the regularization parameter continuously, which increases the efficiency of computation procedure by avoiding the attempt of the regularization parameter. Experimental results show that the proposed algorithm improves the quality of reconstruction image by fixing on the optimization parameter rapidly. Secondly, a reconstruction algorithm from limited-angle based on two-step iterative method is introduced. The iterative method begins with the initial vectors which are obtained through ART algorithm. Experimental results show that the proposed algorithm works effectively.