Processor for endoscope and endoscope system
By calculating the characteristic values of the endoscopic processor, calculating typical values, and performing multinomial regression analysis in the integration unit, the influence of typical assessment values is adjusted, which solves the accuracy and stability problems of existing endoscopic systems in assessing the degree of lesion progression and achieves high-precision lesion progression assessment.
CN115190775BActive Publication Date: 2026-02-27宾得医疗有限责任公司
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Patent Information
- Application Number
- CN202180017682.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Priority Date
- 2020-09-28
- Filing Date
- 2021-09-01
- Publication Date
- 2026-02-27
- Estimated Expiration
- 2041-09-01
AI Technical Summary
Technical Problem
Existing endoscopic systems have limitations in assessing the progression of lesions in biopsy sites, including low accuracy and susceptibility to changes in camera position, leading to unstable and erroneous assessment results.
Method used
Using an endoscopic processor, through a characteristic calculation unit, a typical value calculation unit, and an integration unit, the influence of typical assessment values is adjusted by multinomial regression analysis and camera position information processing to stably calculate the severity of lesions.
Benefits of technology
It enables stable and high-precision assessment of the progression of lesions in living tissue regardless of the camera position, reducing the impact of errors and subjective judgment.
✦ Generated by Eureka AI based on patent content.
Abstract
An endoscope treatment instrument includes an image processing unit for calculating a severity of a lesion indicating a degree of progression of a lesion of a living tissue with one value. The image processing unit includes a feature amount calculation section configured to calculate, for each pixel, a first pixel evaluation value indicating a degree of a first feature representing an appearance of a lesion site from an image; a typical value calculation section configured to calculate a first typical evaluation value by aggregating the first pixel evaluation values; and a combination section configured to adjust, at least according to color component information of the image, an influence degree of the first typical evaluation value indicating that the severity changes with a change in the first typical evaluation value, or to adjust, at least according to a second typical evaluation value obtained by aggregating second pixel evaluation values indicating a degree of a second feature different from the first feature, or to calculate the severity of the lesion by using the adjusted influence degree, at least according to the first typical evaluation value.
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