Medical Image Classification With Interactive Key Image Reselection
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Solution Overview
Problem
Existing medical image processing systems burden doctors with the time-consuming task of selecting key images for reports due to inappropriate automatic image selection, inability to reflect doctor's preferences, and challenges with special examinations.
Innovation Solution
A medical image processing apparatus that classifies images into categories using a trained CNN model, displays automatically selected images, allows user input for reselection, and switches to non-automatically selected images based on category and diagnostic usefulness, reducing the doctor's workload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automatic image selection is implemented, then productivity is improved, but reliability deteriorates due to inference errors and inability to reflect doctor's preferences
Solution Approach 1:
The patent introduces an intermediary review mechanism where automatically selected key images are first presented to the doctor for verification. The doctor can approve or reject selections, and rejected images are re-selected from alternative candidates. This intermediary step bridges the gap between automated efficiency and reliable accuracy, allowing the system to benefit from both automatic selection speed and human judgment precision.
2Reliability
If doctor manually selects key images, then reliability is improved, but productivity deteriorates due to time-consuming work
Solution Approach 1:
The system performs preliminary action by automatically pre-selecting key images based on diagnostic criteria and examination data before presenting them to the doctor. This preliminary selection filters out obviously inappropriate images and prepares a shortlist of candidates, reducing the doctor's workload from reviewing all examination images to merely verifying or selecting from pre-filtered options.
3Ease of operation
If automatic image selection is used, then ease of operation is improved, but adaptability deteriorates due to inability to handle special examinations
Solution Approach 1:
The patent implements dynamics by making the automatic selection criteria adjustable and adaptable. The system can learn from doctor feedback and modify selection parameters based on different examination types and special cases. This allows the system to maintain ease of operation while adapting to various examination scenarios through dynamic parameter adjustment rather than fixed rigid criteria.
Data Source
AI summary
A medical image processing apparatus includes: an image acquisition unit that acquires a plurality of medical images; an image classification unit that classifies the medical images into at least one of a plurality of categories; an image display unit that displays, on a screen, at least one of the plurality of medical images based on a result of the classification as an automatically selected image; an input receiving unit that receives an input from a user to select an image requiring reselection as a key image from among the displayed automatically selected images as a selected image; and a display control unit that switches and displays, as a switching image, a non-automatically selected image other than the automatically selected image among the plurality of medical images classified into each category, instead of displaying the selected image.