Abstract
In the modern medical diagnosis, digital medical images can provide physicians with a more accurate, visualized, and three-dimensional view of various tissues. These images assist in predicting, diagnosing, and treating diseases. However, medical images are highly susceptible to noise contamination from the influence of imaging equipment and the capture process, which poses a significant challenge in the analysis of medical images. This review summarizes the image processing technologies applied in endoscopy, such as image denoising, image deblurring, image enhancement, and image segmentation, involving traditional computational models and deep learning algorithms used in these technologies. Additionally, the clinical applications of these techniques are also discussed.
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