Geometric artifacts reduction for cone-beam CT via L0-norm minimization without dedicated phantoms

Abstract

For cone-beam computed tomography (CBCT), transversal shifts of the rotation center exist inevitably, which will result in geometric artifacts in CT images. In this work, we propose a novel geometric calibration method for CBCT, which can also be used in micro-CT. The symmetry property of the sinogram is used for the first calibration, and then L0-norm of the gradient image from the reconstructed image is used as the cost function to be minimized for the second calibration. An iterative search method is adopted to pursue the local minimum of the L0-norm minimization problem. The transversal shift value is updated with affirmatory step size within a search range determined by the first calibration. In addition, graphic processing unit (GPU)-based FDK algorithm and acceleration techniques are designed to accelerate the calibration process of the presented new method. In simulation experiments, the mean absolute difference (MAD) and the standard deviation (SD) of the transversal shift value were less than 0.2 pixels between the noise-free and noisy projection images, which indicated highly accurate calibration applying the new calibration method. In real data experiments, the smaller entropies of the corrected images also indicated that higher resolution image was acquired using the corrected projection data and the textures were well protected. Study results also support the feasibility of applying the proposed method to other imaging modalities.