Wound identification detection method and system based on deep reinforcement learning, and cloud platform
Through deep reinforcement learning methods, combined with tissue damage assignment and area information of wound images, the wound similarity value is calculated, which solves the problem of inaccurate calculation of the dosage of medicines in the prior art, and achieves a more accurate wound treatment plan.
Patent Information
- Application Number
- CN202510182545.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-19
- Publication Date
- 2025-03-21
- Estimated Expiration
- 2045-02-19
AI Technical Summary
The existing wound identification detection method based on deep reinforcement learning fails to comprehensively consider the degree and area of wound tissue damage, which makes it difficult to accurately calculate the dosage of the drug and cannot better meet the specific needs of patients.
Through a method based on deep reinforcement learning, the tissue damage assignment results of all types of wound extracting information of the preset database and the wound image to be detected are obtained, and the comprehensive tissue damage value and wound similarity value are calculated, and the optimal amount of medicine for each wound image to be detected is finally accurately determined.
The comprehensive degree and area of tissue damage of each wound image to be detected is achieved, and the optimal dosage of medical prescribed drugs is accurately obtained, the treatment effect is improved, and the specific needs of patients are met.