An adaptive multi-photon endoscopy assisted diagnosis method and system based on multi-modal image processing

CN122115459APending Publication Date: 2026-05-29JIMEI UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
JIMEI UNIV
Filing Date
2026-04-29
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Under real-time imaging conditions, existing multimodal image processing methods cannot guarantee the stability of imaging quality and diagnostic reliability, resulting in motion artifacts, local blurring, and incomplete multi-channel information, which affects the real-time diagnosis and assessment of colorectal tumors.

Method used

Multi-photon imaging signals are acquired in real time using a multi-photon endoscope. Consistent regions of interest are selected, and parameters are optimized using an image quality evaluation function to enhance image quality. The images are then input into an auxiliary diagnostic model for detection, ensuring real-time performance and information integrity.

Benefits of technology

It improves the stability and accuracy of colorectal tumor invasion identification, reduces noise interference, enhances the effectiveness of multimodal fusion, and meets the needs of real-time diagnosis.

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Abstract

The application discloses a kind of adaptive multi-photon endoscopy assisted diagnosis method, system based on multi-modal image processing, the method includes: multi-modal photon imaging signal is based on image brightness and is screened to candidate region of interest, and consistent region of interest is screened according to the consistency index of the multi-modal photon imaging signal of candidate region of interest;Image feature extraction is carried out to each consistent region of interest, and the image quality score value of each consistent region of interest is calculated;Based on the image feature and image quality score value of each consistent region of interest, under the condition that image real-time and information integrity constraint are satisfied, determine image optimization parameter, so that the image quality gain after fusion is maximized;Based on the optimization strategy of consistent region of interest, screen the region of interest to be optimized, execute optimization strategy to the region of interest to be optimized and obtain enhanced image, input enhanced image into auxiliary diagnosis model for detection, and output detection result.
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