Abstract: To the problem of sparse angular projection data of CT image reconstruction, TV-ART algorithm introduces the gradient sparse prior knowledge of image to algebraic reconstruction, and the local smooth image gets a better reconstruction effect. However, the algorithm generates step effect when the borders are reconstructed, affecting the quality of the reconstruction. Therefore, this paper proposes an adaptive kernel regression function combined with Algebraic Reconstruction Technique reconstruction algorithm (LAKR-ART), it does not produce the step effect on the border reconstruction, and has a better effect to detail reconstruction. Finally we use the shepp-logan CT image and the actual CT image to make the simulation experiment, and compare with ART and TV-ART algorithm. The experimental results show the algorithm is of effectiveness.
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Key words: image reconstruction, algebraic reconstruction technique, incomplete projection, compressed sensing, adaptive kernel regression