Medical Image Process Recommendation Using Reference Cases and Logs
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Solution Overview
Problem
Existing image processing systems, both cloud-based and on-premises, face challenges in efficiently prompting necessary processing requests without omission, leading to potential oversight and reduced diagnostic accuracy due to high operation load and user forgetfulness.
Innovation Solution
An image processing apparatus and method that acquires image features, references cases, and diagnostic logs to determine and present recommended processes, including automatic lesion extraction and disease determination, using Dicom tag information and similar image search, to improve diagnostic accuracy by prompting processing requests more easily and accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a user selects a process to be executed from among a large number of processes, then the number of available processes increases, but the operation load of selecting a process increases and execution may be postponed
Solution Approach 1:
The system automatically determines and presents recommended processes based on image features, reference cases, and diagnostic logs without requiring manual selection by the user. The processor autonomously analyzes the medical image and generates process recommendations, making the system self-serve the user's needs.
Solution Approach 2:
The manual mechanical process of user selection is replaced with an automated information processing system. The processor uses image feature analysis, reference case matching, and diagnostic log retrieval to automatically determine recommended processes, substituting human cognitive effort with computational analysis.
2Adaptability or versatility
If a user selects a process to be executed from among a large number of processes, then the number of available processes increases, but the user may forget the necessary processing
Solution Approach 1:
The system retrieves diagnostic logs that contain information about necessary processing steps and uses this feedback to determine recommended processes. The processor continuously refines process recommendations based on feedback from reference cases and diagnostic logs, ensuring completeness of necessary processing.
Solution Approach 2:
The system performs preliminary analysis of image features and retrieves relevant reference cases and diagnostic logs before presenting process recommendations. This preliminary action ensures that all necessary processing steps are identified and recommended before the user executes any processes, preventing omissions.
3Reliability
If automated process recommendation is implemented, then diagnostic accuracy is improved, but system complexity increases
Solution Approach 1:
The system segments the complex diagnostic support function into distinct modular components: image feature acquisition, reference case retrieval, diagnostic log retrieval, recommended process determination, and presentation. Each module performs a specific function, making the overall complex system manageable and maintainable through clear separation of concerns.
Data Source
AI summary
Provided are an image processing apparatus, an image processing method and program, and an image processing system that improve diagnostic accuracy by prompting processing requests more easily and without omission. The above object is achieved by the image processing apparatus, the image processing method and program, and the image processing system configured to acquire image features of a medical image of an examination target, acquire a reference case and a diagnostic log based on the image features, determine a recommended process for the medical image of the examination target based on the acquired reference case and diagnostic log, and present the recommended process.