Esophageal mucosa flatness quantification method and device, terminal and storage medium

Abstract

The invention provides an esophageal mucosa flatness quantification method and device, a terminal and a storage medium, and the method comprises the steps: carrying out the conversion of an RGB color space mode of a pre-obtained first dyeing amplification image of a to-be-detected esophageal mucosa, and obtaining a second dyeing amplification image of an HSI color space mode; acquiring a third dyeing magnified image corresponding to the target channel in the second dyeing magnified image; acquiring the image entropy of the third dyeing magnified image; acquiring the image curvature of the third dyeing magnified image; acquiring the surface roughness of the third dyeing magnified image; and quantifying the flatness of the esophageal mucosa to be detected based on the image entropy, the image curvature and the surface roughness. The esophageal mucosa flatness quantification is realized, and the esophageal mucosa flatness identification effect and accuracy are improved.

Description

technical field [0001] The present application relates to the field of auxiliary medical technology, in particular to a method, device and computer-readable storage medium for quantifying the flatness of esophageal mucosa. Background technique [0002] At present, esophagogastroscopy screening is an important means of detecting esophageal cancer, which can detect early esophageal cancer, and surgical resection is the main method of diagnosis and treatment of esophageal cancer. The degree of preoperative lesion infiltration is related to the determination of surgical treatment plan, and the more accurate the judgment of infiltration depth is , The higher the surgical resection rate. [0003] When the surface of an early esophageal cancer is smooth and flat, it is more likely to be mucosal rather than submucosal. Lesions with visible endoscopic features, such as nodules, herniated, or ulcerated lesions, are more likely to be submucosal carcinomas. That is, according to the j...

AI Technical Summary

Problems solved by technology

That is, according to the judgment of the smoothness of the lesion surface, the accurate judgment of the infiltration depth of esophageal cancer can be realized. However, the existing identification of the flatness of the esophageal mucosa is poor and the accuracy is low, which is likely to affect the subsequent judgment of the infiltration depth of esophageal cancer.

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