Curvature constraint based image reconstruction for limited-angle computed tomography

Abstract

Compared with traditional CT with full angular scan, limited-angle CT has advantages in scanning plateshaped objects and reducing imaging dose. But image reconstruction from limited-angle CT is challenging, because the acquired data are not complete. In this abstract, we proposed an imaging model for limited-angle CT, which is an extension of our previous work, where edge information is used to recover the blurred image edges and the distorted gray values of non-edge points. The new model introduces an extra curvature term in the objective function to constraint the length of the edges of the object and thus eliminates the possible jagged artifacts in the images reconstructed with the model proposed earlier. Numerical experiments with real data verify the effectiveness of the proposed imaging model and the corresponding reconstruction algorithm.