Department of Stomatology, Renhe Hospital of China Three Gorges University, Yichang 443000, Hubei Province, China.
Department of Medical Imaging Science, Renhe Hospital of China Three Gorges University, Yichang 443000, Hubei Province, China.
Comput Intell Neurosci. 2022 Sep 19;2022:6041872. doi: 10.1155/2022/6041872. eCollection 2022.
The application of computer vision technology in the medical field provides more accurate technical support for oral disease detection. The research proposes the CT image denoising algorithm based on wavelet and bilateral filtering. Through the study of the imaging principle of CT image and the CT image acquisition scene, the CT image data is filtered by wavelet and bilateral filtering algorithm, and the algorithm is proposed from the peak signal-to-noise ratio, structural similarity, and the effective detection of three-dimensional image construction of the image. The test results show that the proposed algorithm has excellent performance in the aspects of peak signal-to-noise ratio, structural similarity, and error of mean square. When the proportions of Gaussian noise are 10%, 20%, 30%, 40%, and 50%, the MSE error values of the proposed algorithm are 0.002, 0.004, 0.006, and 0.007, respectively, and the performance is the best in the comparison of multiple algorithms. The contents of the research provide an important theoretical reference for the treatment of clinical oral diseases.
计算机视觉技术在医学领域的应用为口腔疾病检测提供了更精确的技术支持。研究提出了基于小波和双边滤波的 CT 图像去噪算法。通过对 CT 图像的成像原理和 CT 图像采集场景的研究，对 CT 图像数据进行了小波和双边滤波算法的滤波处理，从峰值信噪比、结构相似性和三维图像构建的有效检测三个方面提出了算法。实验结果表明，该算法在峰值信噪比、结构相似性和均方误差方面均具有优异的性能。当高斯噪声的比例分别为 10%、20%、30%、40%和 50%时，所提算法的均方误差值分别为 0.002、0.004、0.006 和 0.007，在多种算法的比较中性能最佳。研究内容为临床口腔疾病的治疗提供了重要的理论参考。
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