Endoscope Controller Using Inspection History for Abnormality Alerts
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Solution Overview
Problem
Existing endoscope systems lack an efficient method to notify users of potential abnormalities in inspection targets based on past inspection histories, which can lead to missed detection of issues during subsequent inspections.
Innovation Solution
An endoscope system that includes an image sensor, a display, and a controller connected to an information management apparatus, which performs notification processing by analyzing the inspection history and displaying attention-grabbing notifications when predetermined conditions of abnormality are met, such as a 60% or higher incidence of 'reinspection required' or 'caution needed' in the inspection history.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the endoscope system only displays memorized endoscope images without notification processing, then the system remains simple and easy to operate, but users may miss detecting abnormalities in inspection targets
Solution Approach 1:
The system performs preliminary analysis of inspection history data before the current inspection, pre-identifying abnormal areas and preparing notification criteria. This allows the system to proactively alert users to potential abnormalities rather than waiting for passive observation, thereby improving detection reliability without requiring complex real-time processing during inspection
Solution Approach 2:
The notification processing unit acts as an intermediary between the inspection history data and the user, translating raw historical data into meaningful alerts and annotations. This mediator component filters and prioritizes information, presenting only relevant abnormalities to users, thus improving reliability while maintaining ease of operation
2Productivity
If the system performs comprehensive notification processing based on inspection history, then detection efficiency is improved, but the operation becomes more complex
Solution Approach 1:
The system automatically retrieves and analyzes inspection history data without requiring manual intervention. The notification processing unit autonomously compares current inspection data with historical data, generates alerts, and annotates images based on predetermined criteria, thereby improving detection efficiency while maintaining operational simplicity
Solution Approach 2:
The system provides automated feedback to users through notifications and image annotations that highlight areas requiring attention. This feedback mechanism guides users efficiently through the inspection process by directing their focus to critical areas, improving productivity without increasing operational complexity
3Measurement precision
If the system stores and analyzes detailed inspection history data, then notification accuracy is improved, but information management becomes more complex
Solution Approach 1:
The system extracts only the essential and relevant features from inspection history data, such as abnormal area locations, types of abnormalities, and their characteristics. By extracting only necessary information rather than managing complete raw datasets, the system achieves high notification accuracy while simplifying information management
Solution Approach 2:
The inspection history data is segmented into structured components including inspection target information, abnormal area locations, abnormality types, and temporal data. This segmentation allows the notification processing unit to efficiently query and analyze specific aspects of historical data, improving notification accuracy while maintaining manageable data structures
Data Source
AI summary
An endoscope apparatus includes an image sensor configured to pick up an image of an inspection target, a display configured to display an endoscope image of the inspection target acquired by the image sensor, and a controller configured to perform notification processing to call attention of a user to the endoscope image according to an inspection history that is a history of past inspections of the inspection target and is memorized in a memory.