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In computed tomography (CT), miscalibrated or imperfect detector elements produce stripe artifacts in the sinogram. The stripe artifacts in Radon space are responsible for concentric ring artifacts in the reconstructed images. To remove the ring artifacts from the images, there exist several methods. While most of the methods are performed in the image domain, a few of them are adopted in the projection or sinogram domain. In the latter methods, the sinogram is intended to be corrected before the image reconstruction. In this work, a novel optimization model is proposed to remove the ring artifacts in an iterative reconstruction procedure. To correct a sinogram, a new correcting vector is proposed to compensate for malfunctioning of detectors in the projection domain. Moreover, a novel directional total variation (DTV) based regularization is developed to penalize the ring artifacts in the image domain. The optimization problem is solved by using the alternating minimization scheme (AMS). In each iteration, the fidelity term along with the DTV-based regularization is first solved to find the image, and then the correcting coefficient vector is updated according to the obtained image. Because the sinogram and the image are simultaneously updated, the proposed method basically performs in both the image and sinogram domains. The proposed method is evaluated using real preclinical datasets containing strong ring artifacts , and the experimental results show that the proposed algorithm can efficiently suppress the ring artifacts.
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