Dynamic Medical Information Management for Diagnostic Data Comparison
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Solution Overview
Problem
The challenge lies in effectively utilizing dynamic medical images for diagnosis due to the lack of comprehensive understanding of normal images, increased data volume, and the inefficiency of viewing dynamic images, which are often compared to still images without sufficient quantitative criteria, leading to limited diagnostic efficiency and the need for improved diagnosis support.
Innovation Solution
A medical information management system that associates dynamic information obtained through radiation with non-dynamic information from other imaging modalities and tests, enabling efficient management and comparison of both types of data for enhanced diagnostic support.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If dynamic images are used for diagnosis, then diagnostic information completeness is improved, but information amount and viewing time increase significantly
Solution Approach 1:
The system extracts and highlights only the candidate abnormal parts from the dynamic image sequence, separating the diagnostically relevant information from the redundant normal portions. This allows doctors to focus on specific regions of interest without viewing the entire dynamic image set, thereby reducing viewing time while maintaining diagnostic completeness.
Solution Approach 2:
The system performs preliminary analysis of dynamic images to automatically identify and mark candidate abnormal parts before the doctor views them. By pre-processing the images to highlight potential abnormalities, the system prepares the diagnostic information in advance, reducing the time required for manual review while ensuring no critical information is missed.
2Reliability
If dynamic images are used for diagnosis, then diagnostic capability is improved, but man-hours and operational complexity increase
Solution Approach 1:
The system performs automatic analysis of dynamic images to identify candidate abnormal parts without requiring manual review of the entire image sequence. The automated processing reduces the operational burden on doctors, allowing them to focus their expertise on evaluating the highlighted candidates rather than manually examining every frame, thereby improving ease of operation while maintaining diagnostic capability.
3Measurement precision
If normal dynamic images are collected for comparison, then diagnostic accuracy is improved, but data collection difficulty increases
Solution Approach 1:
The system is designed to handle multiple types of medical data (dynamic images, still images, examination results) through a unified data structure and management approach. This multi-functional capability allows the system to collect and process various data sources using the same infrastructure, reducing the difficulty of data collection while improving diagnostic accuracy through comprehensive comparison.
Data Source
AI summary
A medical information management apparatus including a hardware processor that manages dynamic information and non-dynamic information in association with each other, the dynamic information being obtained by dynamic imaging with radiation to a first subject that satisfies a condition of a predetermined disease, and the non-dynamic information being obtained by imaging other than the dynamic imaging or a test to a second subject that satisfies the condition of the predetermined disease.