Endoscope Image Review With AI Observation Completion Feedback
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Solution Overview
Problem
Existing medical image processing systems face challenges in accurately determining the completion of observation for specific parts during examinations, leading to potential oversight due to discrepancies between artificial intelligence and human judgment, which can result in incomplete or inaccurate assessments.
Innovation Solution
A medical image processing apparatus that includes a processor to make observation completion determinations, display the results, receive user corrections, and reflect those corrections in the display, utilizing features like marks, time presence, and central positioning to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If AI-based observation completion determination is used to suppress oversight of body parts, then productivity is improved, but reliability deteriorates due to discrepancies between AI and human judgment
Solution Approach 1:
The system implements feedback by allowing doctors to provide correction inputs when AI determination results do not match their actual observation status. The correction input receiving unit collects these feedbacks, and the storage unit stores them for future use. This feedback mechanism enables the system to learn from discrepancies between AI judgment and human expertise, improving reliability while maintaining high productivity.
Solution Approach 2:
The system enables self-service by automatically determining observation completion status using AI processing of medical images. The determination unit autonomously analyzes images to identify whether specific body parts have been observed, reducing the need for manual tracking and improving productivity without completely replacing human judgment.
2Ease of operation
If AI determination criteria are used to automatically assess observation completion, then ease of operation is improved, but measurement precision deteriorates due to subjective factors in human judgment
Solution Approach 1:
The feedback mechanism allows doctors to correct AI determination errors, improving measurement precision. The correction inputs serve as ground truth data that helps refine the AI determination criteria over time, bridging the gap between automated simplicity and human expertise accuracy.
Solution Approach 2:
The determination unit acts as an intermediary between automated AI analysis and human judgment. It provides automated determination results that can be reviewed and corrected by doctors, serving as a mediator that combines the efficiency of AI with the precision of human assessment.
3Reliability
If multiple body parts are thoroughly observed to ensure complete examination, then reliability is improved, but loss of time increases due to the complexity of tracking each part
Solution Approach 1:
The AI-based determination unit automatically tracks and determines the observation status of multiple body parts without requiring manual intervention. This self-service approach maintains reliable tracking of examination completeness while eliminating the time-consuming manual tracking process.
Solution Approach 2:
The feedback mechanism ensures that even when time constraints exist, the system can maintain reliable tracking by allowing quick correction inputs from doctors. This feedback loop ensures that time is not lost to manual verification while maintaining examination completeness through automated tracking.
Data Source
AI summary
There are provided a medical image processing apparatus, an endoscope system, a diagnosis assistance method, and a program capable of coping with an erroneous determination while utilizing an observation completion determination in which image processing is used and of suppressing oversight of an observation target part by a doctor. The medical image processing apparatus includes at least one processor. The at least one processor acquires a medical image; makes, on the basis of the medical image, an observation completion determination as to whether observation is completed for a target part; performs display control for causing a determined result of the observation completion determination to be displayed on a display device, receives a user input including an instruction for correcting display content indicating the determined result of the observation completion determination, and causes corrected content based on the user input to be reflected in the display.