CT Image Iterative Reconstruction Method Based on Compressed Sensing

Abstract

The invention discloses a CT image iteration reconstruction method based on compressed sensing and particularly relates to a CT image reconstruction method for carrying out minimization algebra iteration (algebraic reconstruction technique, ART) of the total variation (TV) in a wavelet domain. The method mainly comprises the steps that (1) imaging parameters of a CT system and projection data collected by a scanning system are obtained; (2) the projection data are initialized, and namely, Wiener filtering noise reduction processing and wavelet sparsity conversion are carried out on the projection data; (3) algebra iteration reconstruction is carried out on the initialized projection data on the basis of minimization of the image total variation (TV), and whether the iteration result meets a convergence condition is judged, if not, the iteration reconstruction image data are used as initial values, and iteration continues to be carried out; if yes, reconstructed images are used as final output images. Compared with the traditional filtering back projection and algebra iteration CT image reconstruction technology, the method finishes reconstructing the images with the fewer projection data, the speed for reconstructing the images can be increased, the radiation dose is reduced, and the image reconstruction quality can be improved.

Description

technical field [0001] The present invention relates to the field of image processing of medical images, in particular to the field of X-ray computed tomography, and specifically refers to a method for iterative reconstruction of CT images based on compressed sensing. It can also shorten the image reconstruction time and reduce the radiation dose. Background technique [0002] X-ray computed tomography (Computed Tomography, CT) technology is a digital imaging technology that combines computer technology and radiation detection technology. Because it can obtain high spatial resolution tomographic information, it has been widely used in medical diagnosis and industrial detection. Usually high-quality CT images require a large number of projection views, prolonging the scanning time, and long-term scanning will increase the radiation dose, which may cause deformation or damage to the imaging items. [0003] The traditional CT reconstruction algorithm comes from the Radon tran...

AI Technical Summary

Problems solved by technology

[0005] Technical problem: The object of the present invention is to provide a CT image iterative reconstruction method based on compressed sensing, which overcomes the heavy aliasing artifacts of the reconstructed image under the under-sampled projection data and the reconstruction algorithm consumption of the filtered back projection and the algebraic iterative reconstruction algorithm. It can reduce the scanning time of the CT imaging system and speed up the imaging speed, thereby reducing the mechanical cost and reducing the motion artifact of the object under inspection, and expanding the scope of clinical application

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