A variation-based ring artifact correction method with sparse constraint for flat-detector CT

The reconstructed slice quality of flat-detector computed tomography (CT) is often disturbed by concentric-ring artifacts. Since concentric rings in CT slices appear as straight stripes when transformed into polar coordinates, a variation-based model is proposed to suppress the stripes. The method is motivated by two observations about stripes in polar coordinates: (1) ring artifacts attenuate gradually along the radial direction, leading to a sparse distribution of stripes and (2) stripes greatly distort the image gradient across the stripes, while slightly affecting the image gradient along the stripes. Thus, a l(1)-norm-based data fidelity term and a l(0)-norm/l(1)-norm unidirectional variation-based regularization term are presented to characterize the stripes. The alternating direction method of multipliers is introduced to solve the resulting minimization problem. Moreover, we discuss the interpolation methods used in coordinate transformation and find that the nearest neighbor interpolation is optimal. Experimental results on simulated and real data demonstrate that our method can correct ring artifacts effectively compared with state-of-the-art coordinate transformation-based methods, as well as preserve the structures and details of slices.