Dynamic Image Processing Device for Automated Teaching File Organization
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Solution Overview
Problem
The inefficiency in organizing and creating teaching files using dynamic images due to the higher amount of information compared to still images, resulting in time and effort-intensive processes.
Innovation Solution
A dynamic image processing device and method that acquires dynamic images, judges disease candidates based on the images, and determines the storage location of the images based on the judged candidates, utilizing a hardware processor and machine learning for efficient processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dynamic images are used in case collections to improve knowledge, then the educational value is improved, but the time and effort required to organize and create teaching files increases
Solution Approach 1:
The system enables dynamic images to automatically categorize and organize themselves into appropriate teaching files through AI-based disease candidate judgment. The images autonomously determine their own storage locations without requiring manual sorting by educators, thus preserving educational value while eliminating the time-consuming organization process.
Solution Approach 2:
The system performs preliminary classification of dynamic images into disease categories during the image acquisition phase. By pre-judging disease candidates and determining storage locations before the teaching file creation process, the system eliminates the need for subsequent manual organization, reducing both time and effort while maintaining high educational quality.
2Loss of information
If dynamic images are used instead of still images, then more comprehensive medical information is captured, but the complexity of processing and organizing the images increases
Solution Approach 1:
The system introduces an AI-based disease candidate judgment module as an intermediary between dynamic image acquisition and storage. This intermediary automatically analyzes the complex dynamic image data, extracts disease-relevant information, and determines appropriate storage locations, thereby preserving complete medical information while simplifying the overall processing workflow through automated intelligence.
3Measurement precision
If manual organization of dynamic images is performed, then accurate categorization can be achieved, but productivity decreases due to time-consuming manual processes
Solution Approach 1:
The system replaces the mechanical manual organization process with an automated AI-based disease candidate judgment system. The hardware processor automatically analyzes dynamic images, judges disease candidates, and determines storage locations, achieving both high categorization accuracy through intelligent analysis and high productivity through automation, thereby eliminating the trade-off between precision and speed.
Data Source
AI summary
A dynamic image processing device includes a hardware processor. The hardware processor acquires a dynamic image, judges a disease candidate based on the dynamic image, and determines a storage location of the dynamic image based on the disease candidate. In one embodiment, the hardware processor judges the disease candidate based on an analysis result of the dynamic image.