Iterative image-domain ring artifact removal in cone-beam CT

Abstract

Ring artifacts in cone beam computed tomography (CBCT) images are caused by pixel gain variations using flat-panel detectors, and may lead to structured non-uniformities and deterioration of image quality. The purpose of this study is to propose a method of general ring artifact removal in CBCT images. This method is based on the polar coordinate system, where the ring artifacts manifest as stripe artifacts. Using relative total variation, the CBCT images are first smoothed to generate template images with fewer image details and ring artifacts. By subtracting the template images from the CBCT images, residual images with image details and ring artifacts are generated. As the ring artifact manifests as a stripe artifact in a polar coordinate system, the artifact image can be extracted by mean value from the residual image; the image details are generated by subtracting the artifact image from the residual image. Finally, the image details are compensated to the template image to generate the corrected images. The proposed framework is iterated until the differences in the extracted ring artifacts are minimized. We use a 3D Shepp-Logan phantom, Catphan©504 phantom, uniform acrylic cylinder, and images from a head patient to evaluate the proposed method. In the experiments using simulated data, the spatial uniformity is increased by 1.68 times and the structural similarity index is increased from 87.12% to 95.50% using the proposed method. In the experiment using clinical data, our method shows high efficiency in ring artifact removal while preserving the image structure and detail. The iterative approach we propose for ring artifact removal in cone-beam CT is practical and attractive for CBCT guided radiation therapy.

A consistency evaluation of signal-to-noise ratio in the quality assessment of human brain magnetic resonance images

“…The full-reference algorithms require the access to the reference image, while it is often unavailable in the medical imaging domain. To tackle this problem, the images from advanced devices are used as the reference to validate the proposed methods with images from common devices [ 24 , 25 ]. However, this kind of approaches leads to new obstacles due to uncontrollable motion and particularly the different imaging characteristics.…”

Ring Artifacts Reduction in CBCT: Pixels Detection and Patch Based Correction

“…Among them, the first column is the original images, the second column is the corrected images, the third column is the residual images, and the fourth column is the zoomed image details. We compare the proposed algorithm with several state-of-the-art ring removal methods via sinogram domain, including polar coordinate based method [9], wavelet-Fourier correction [13], GAN-based method [11], median filtering-based method [19], and polynomial interpolation method [20], and the correction images are shown in Fig. 6, of which all images are set with the same window width and level, and the first column in each row is in original size, the 2 nd and 3 rd column are the enlarged part of the original one.…”

“…However, it is hard for keeping same resolution due to interpolation during the transformation via different coordinate systems. Xiao et al proposed a method [9] for extracting ring artifacts in polar coordinates, though the image resolution is kept well, but it may not be suitable for the complicated scenario as it supposes that the ring artifacts in the θ direction have the same gray value. The dictionary representation [10] and the deep learning based methods [11] are also used in reconstructed images.…”

Efficient Segmentation of a Breast in B-Mode Ultrasound Tomography Using Three-Dimensional GrabCut (GC3D)

“…It should be recognized that removing the distorted images is necessary ( Figure 1 ). It is known to us that artifact removal is extremely difficult in medical imaging [ 61 ], and the most fundamental solution comes from the upgrading of imaging devices [ 62 , 63 ]. Therefore, in this paper, we followed previous studies [ 9 , 12 , 13 ] to define the starting and the ending slice.…”