Intelligent osteosarcoma image recognition and classification method and system based on image recognition model

By employing an image recognition model-based approach, and utilizing techniques such as multi-sequence perturbation equalization enhancement and color space transformation remapping, combined with tumor edge features and metabolic state analysis, the accuracy and consistency issues of osteosarcoma image recognition were resolved, achieving efficient and precise image data processing.

CN121725271APending Publication Date: 2026-03-24NANHUA HOSPITAL AFFILIATED TO UNIV OF SOUTH CHINA
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Patent Information

Application Number
CN202511613361.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-11-06
Publication Date
2026-03-24

AI Technical Summary

Technical Problem

Existing methods for osteosarcoma image recognition and classification rely on manual analysis, resulting in low accuracy and consistency. They are also difficult to process complex image data, have low feature extraction efficiency, and lack systematicity in feature reconstruction and classification judgment, leading to misdiagnosis and missed diagnosis.

Method used

An image recognition model-based approach is adopted, which uses multi-sequence perturbation equalization enhancement, color space transformation and remapping, tumor region extraction and contrast inversion processing, combined with a preset image recognition model to identify tumor edge features. Then, the metabolite signal features around the tumor are analyzed through benign tumor images to generate metabolic difference data for classification and correction.

Benefits of technology

It improves the accuracy and reliability of osteosarcoma image recognition, optimizes the image processing workflow, reduces subjective interference, enhances the objectivity and systematicness of data analysis, and promotes the in-depth application of intelligent recognition technology in the field of medical imaging.

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Abstract

The invention relates to the technical field of image recognition, in particular to an osteosarcoma image intelligent recognition and classification method and system based on an image recognition model. The method comprises the following steps: collecting a tumor image and carrying out multi-sequence disturbance equilibrium enhancement to generate an enhanced block tumor image, then obtaining a color standardized image through color space transformation remapping, then extracting a tumor region image and carrying out contrast inversion processing, reconstructing a tumor feature image, and finally, carrying out multi-sequence disturbance equilibrium enhancement on the tumor feature image. Based on a preset image recognition model, tumor edge features are recognized, the edge rule degree is determined, preliminary classification is carried out, a benign tumor image is obtained, surrounding metabolite signal features of the benign tumor image are analyzed, a benign reference group is formed through combination, metabolism state comparison is carried out on tumor feature images, and metabolism difference data are generated. And performing category correction according to the metabolic state mapping data so as to identify the osteosarcoma category. According to the invention, intelligent analysis of tumor features is realized, the image processing flow is optimized, and the processing efficiency is improved.
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