OS-EM reconstruction using blank region as priors for artifacts reduction in Cone-beam CT

摘要

Traditional computed tomography reconstructions are limited by many kinds of artifacts. In general, they give dissatisfactory image. To reduce image noise and artifacts, we propose an iterative approach processing these reconstructed images, which are acquired by analytical inversion methods. In this paper, we describe ordered subsets expectation maximization (OS-EM) algorithms. Our reconstruction algorithm is based on a maximum a posteriori (MAP) approach, which allows us to incorporate priori information to stabilize the EM algorithm. The OS-EM algorithm provides good quality reconstructions after only a few iterations, yet beyond a critical number of iterations, the artifact is magnified due to inherent instability problem of OS-EM. To overcome this problem, we estimate the number of iterations by using priori information, the priori information is the blank region in the projection data resulting from a part of X-ray's air scan. In ideal case these corresponding regions in reconstructed image should also be blank. But in practice, they are not blank any more due to containing noise and artifacts. Based on this prior information, we can obtain an optimum number of iterations in the small air scan region. We process the whole estimated image with the same number of iterations. The two processes are carried on at the same time. Then the resulting image is considered as the best restoration of the original image. Experiments show that by our method, the artifacts and noise can be greatly suppressed and the contrast can be significantly improved.