Eldib Mohamed Elsayed, Hegazy Mohamed, Mun Yang Ji, Cho Myung Hye, Cho Min Hyoung, Lee Soo Yeol
Department of Biomedical Engineering, Kyung Hee University, Yongin, Gyeonggi 17104, Korea.
Sensors (Basel). 2017 Jan 30;17(2):269. doi: 10.3390/s17020269.
We introduce an efficient ring artifact correction method for a cone-beam computed tomography (CT). In the first step, we correct the defective pixels whose values are close to zero or saturated in the projection domain. In the second step, we compute the mean value at each detector element along the view angle in the sinogram to obtain the one-dimensional (1D) mean vector, and we then compute the 1D correction vector by taking inverse of the mean vector. We multiply the correction vector with the sinogram row by row over all view angles. In the third step, we apply a Gaussian filter on the difference image between the original CT image and the corrected CT image obtained in the previous step. The filtered difference image is added to the corrected CT image to compensate the possible contrast anomaly that may appear due to the contrast change in the sinogram after removing stripe artifacts. We applied the proposed method to the projection data acquired by two flat-panel detectors (FPDs) and a silicon-based photon-counting X-ray detector (PCXD). Micro-CT imaging experiments of phantoms and a small animal have shown that the proposed method can greatly reduce ring artifacts regardless of detector types. Despite the great reduction of ring artifacts, the proposed method does not compromise the original spatial resolution and contrast.
我们介绍了一种用于锥束计算机断层扫描(CT)的高效环形伪影校正方法。第一步,我们校正投影域中值接近零或饱和的缺陷像素。第二步,我们计算正弦图中沿视角方向每个探测器元件的平均值,以获得一维(1D)平均向量,然后通过求平均向量的逆来计算1D校正向量。我们在所有视角上逐行将校正向量与正弦图相乘。第三步,我们对原始CT图像与上一步获得的校正后CT图像之间的差异图像应用高斯滤波器。将滤波后的差异图像添加到校正后的CT图像中,以补偿由于去除条纹伪影后正弦图中的对比度变化可能出现的对比度异常。我们将所提出的方法应用于由两个平板探测器(FPD)和一个基于硅的光子计数X射线探测器(PCXD)采集的投影数据。对体模和小动物的微型CT成像实验表明,无论探测器类型如何,所提出的方法都能大大减少环形伪影。尽管环形伪影大大减少,但所提出的方法不会损害原始的空间分辨率和对比度。