Beijing Key Laboratory of Intelligent Information Technology, School of Computer Science and Technology, Beijing Institute of Technology, Beijing, 100081, China.
School of Science, Tianjin University, Tianjin, 300072, China.
Med Phys. 2019 Apr;46(4):1719-1727. doi: 10.1002/mp.13430. Epub 2019 Feb 22.
It often happens that cone-beam corrupted tomography (CBCT) images have some ring artifacts due to the inconsistent response of detector pixels. Removing ring artifacts in CBCT images without impairing the image quality is critical. The purpose of this study is to implement a whole new method of removing ring artifacts in CBCT images based on TV-Stokes denoising equation and unidirectional total variation (UTV).
This method is based on the polar coordinates, where the ring artifacts are shown as horizontal parallel stripes. To begin with, we design a UTV model with the constraint of zero divergence condition to only smooth vertical tangent vectors, and keep horizontal tangent vectors unchanged. In turn, the corresponding smooth normal vectors can be obtained. Next, in order to reconstruct the clean image that fits the obtained normal vectors, the UTV model about the potential clean image is added to the original TV-Stokes denoising equation.
Our method was applied to simulated data and real corrupted data to verify its performance. High-quality corrected images without ring artifacts were obtained. In the simulated experiments, our method is not only able to obtain the most complete corrected images, but also capable of acquiring the best quantitative assessments among several different methods. In the experiments of real data, the proposed method was effective in removing ring artifacts and in preserving the original details. Comparative results on several experiments illustrated that our algorithm corrects ring artifacts effectively and outperforms the two compared methods on objective indices and subjective image quality.
Benefiting from the TV-Stokes equation and the UTV model, the proposed scheme can be effectively applied to remove ring artifacts in CBCT images, simultaneously preserving the original image details and structure well. Furthermore, this new algorithm can be applied directly on reconstructed images, thus eliminating the requirement for additional imaging data.
由于探测器像素响应不一致，锥形束 CT（CBCT）图像经常会出现一些环状伪影。在不损害图像质量的情况下，去除 CBCT 图像中的环状伪影至关重要。本研究旨在基于 TV-Stokes 去噪方程和单向全变分（UTV），实现一种全新的去除 CBCT 图像环状伪影的方法。
该方法基于极坐标，其中环状伪影表现为水平平行条纹。首先，我们设计了一个 UTV 模型，该模型的约束条件为零散度条件，仅对垂直切向量进行平滑，保持水平切向量不变。然后，可以得到相应的平滑法向量。接下来，为了重建符合所得到的法向量的干净图像，在原始 TV-Stokes 去噪方程中添加关于潜在干净图像的 UTV 模型。
我们的方法应用于模拟数据和真实的污染数据，以验证其性能。得到了没有环状伪影的高质量校正图像。在模拟实验中，我们的方法不仅能够获得最完整的校正图像，而且能够在几种不同方法中获得最佳的定量评估。在真实数据的实验中，所提出的方法有效地去除了环状伪影，并保留了原始细节。对几个实验的比较结果表明，我们的算法可以有效地去除环状伪影，在客观指标和主观图像质量方面优于两种比较方法。
受益于 TV-Stokes 方程和 UTV 模型，所提出的方案可以有效地应用于去除 CBCT 图像中的环状伪影，同时很好地保留原始图像的细节和结构。此外，该新算法可以直接应用于重建图像，从而消除对额外成像数据的需求。
