Kasai Ryosuke, Otsuka Hideki
Department of Medical Imaging/Nuclear Medicine, Institute of Biomedical Sciences, Tokushima University, 3-18-15 Kuramoto, Tokushima 770-8509, Japan.
Diagnostics (Basel). 2023 Mar 15;13(6):1111. doi: 10.3390/diagnostics13061111.
Coronary computed tomography angiography (CCTA) is widely used due to its improvements in computed tomography (CT) diagnostic performance. Unlike other CT examinations, CCTA requires shorter rotation times of the X-ray tube, improving the temporal resolution and facilitating the imaging of the beating heart in a stationary state. However, reconstructed CT images, including those of the coronary arteries, contain insufficient X-ray photons and considerable noise. In this study, we introduce an image-processing technique for noise reduction using singular value decomposition (SVD) for CCTA images. The threshold of SVD was determined on the basis of minimization of Jensen-Shannon (JS) divergence. Experiments were performed with various numerical phantoms and varying levels of noise to reduce noise in clinical CCTA images using the determined threshold value. The numerical phantoms produced 10% higher-quality images than the conventional noise reduction method when compared on a quantitative SSIM basis. The threshold value determined by minimizing the JS-divergence was found to be useful for efficient noise reduction in actual clinical images, depending on the level of noise.
冠状动脉计算机断层血管造影（CCTA）因其在计算机断层扫描（CT）诊断性能方面的改进而被广泛应用。与其他CT检查不同，CCTA需要X射线管更短的旋转时间，以提高时间分辨率并便于在静止状态下对跳动的心脏进行成像。然而，重建的CT图像，包括冠状动脉的图像，包含的X射线光子不足且噪声相当大。在本研究中，我们介绍了一种使用奇异值分解（SVD）对CCTA图像进行降噪的图像处理技术。SVD的阈值是基于詹森-香农（JS）散度的最小化来确定的。使用确定的阈值对各种数值模型和不同噪声水平进行了实验，以降低临床CCTA图像中的噪声。在基于定量结构相似性指数测量（SSIM）进行比较时，数值模型生成的图像质量比传统降噪方法高出10%。发现通过最小化JS散度确定的阈值对于根据噪声水平在实际临床图像中进行有效降噪很有用。
