ArticleComputational intelligence and neuroscience2022
Oral CT Image Processing Based on Oral CT Image Filtering Algorithm.
Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Deep Learning-Based Super-Resolution Reconstruction on Undersampled Brain Diffusion-Weighted MRI for Infarction Stroke: A Comparison to Conventional Iterative Reconstruction.AJNR. American journal of neuroradiology · 2025Article
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Authors and funding
6 authors.
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Abstract
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.
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