Qu Xiaolei, Lai Chao-Jen, Zhong Yuncheng, Yi Ying, Shaw Chris C
Graduate School of Engineering, The University of Tokyo, Tokyo, Japan.
Department of Imaging Physics, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.
Int J Comput Assist Radiol Surg. 2016 Jul;11(7):1233-46. doi: 10.1007/s11548-015-1317-8. Epub 2015 Oct 29.
Cone-beam breast computed tomography (CBBCT), a promising breast cancer diagnostic technique, has been under investigation for the past decade. However, owing to scattered radiation and beam hardening, CT numbers are not uniform on CBBCT images. This is known as cupping artifact, and it presents an obstacle for threshold-based volume segmentation. In this study, we proposed a general post-reconstruction method for cupping artifact correction.
There were four steps in the proposed method. First, three types of local region histogram peaks were calculated: adipose peaks with low CT numbers, glandular peaks with high CT numbers, and unidentified peaks. Second, a linear discriminant analysis classifier, which was trained by identified adipose and glandular peaks, was employed to identify the unidentified peaks as adipose or glandular peaks. Third, adipose background signal profile was fitted according to the adipose peaks using the least squares method. Finally, the adipose background signal profile was subtracted from original image to obtain cupping corrected image
In experimental study, standard deviation of adipose tissue CT numbers was obviously reduced and the CT numbers were more uniform after cupping correction by proposed method; in simulation study, root-mean-square errors were significantly reduced for both symmetric and asymmetric cupping artifacts, indicating that the proposed method was effective to both artifacts.
A general method without a circularly symmetric assumption was proposed to correct cupping artifacts in CBBCT images for breast. It may be properly applied to images of real patient breasts with natural pendent geometry.
锥形束乳腺计算机断层扫描（CBBCT）是一种很有前景的乳腺癌诊断技术，在过去十年中一直在研究。然而，由于散射辐射和束硬化，CBBCT图像上的CT值并不均匀。这被称为杯状伪影，它给基于阈值的体积分割带来了障碍。在本研究中，我们提出了一种用于杯状伪影校正的通用重建后方法。
所提出的方法有四个步骤。首先，计算三种类型的局部区域直方图峰值：低CT值的脂肪峰值、高CT值的腺体峰值和未识别的峰值。其次，使用由已识别的脂肪和腺体峰值训练的线性判别分析分类器，将未识别的峰值识别为脂肪或腺体峰值。第三，使用最小二乘法根据脂肪峰值拟合脂肪背景信号轮廓。最后，从原始图像中减去脂肪背景信号轮廓以获得杯状伪影校正后的图像。
在实验研究中，通过所提出的方法进行杯状伪影校正后，脂肪组织CT值的标准差明显降低，CT值更加均匀；在模拟研究中，对称和不对称杯状伪影的均方根误差均显著降低，表明所提出的方法对两种伪影均有效。
提出了一种无需圆对称假设的通用方法来校正乳腺CBBCT图像中的杯状伪影。它可以适当地应用于具有自然下垂几何形状的真实患者乳房的图像。
