Medical Image Display Workflow for Complete AI Lesion Analysis
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Solution Overview
Problem
Existing medical imaging systems relying on AI for lesion detection face challenges in ensuring timely and reliable interpretation results, leading to potential delays and quality issues, which can result in doctors overlooking lesions due to incomplete or unavailable AI analysis.
Innovation Solution
A medical information display apparatus and method that includes a hardware processor to obtain lesion detection results and execute a prevention function to prevent inappropriate interpretation by users, ensuring that interpretation is only performed after the AI analysis is complete and accurate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the AI interpretation process is performed on medical images, then the accuracy of lesion detection is improved, but the time required for interpretation increases
Solution Approach 1:
The system performs preliminary actions by displaying workflow information and analysis status to users before the AI interpretation is complete. This allows users to understand the current state of analysis and prepare appropriately, reducing unnecessary waiting time while maintaining accurate interpretation results.
Solution Approach 2:
The system implements feedback by providing real-time updates on the AI analysis status, including workflow progress and expected completion time. This feedback mechanism allows users to monitor the interpretation process and make informed decisions about whether to wait or proceed with preliminary review, optimizing the balance between accuracy and time efficiency.
2Reliability
If the doctor waits for the AI interpretation result, then the quality of interpretation is improved, but the productivity decreases
Solution Approach 1:
The system applies dynamics by allowing flexible interpretation workflows where doctors can adapt their behavior based on real-time AI analysis status. Doctors can choose to wait for complete AI results when quality is critical, or proceed with preliminary review when productivity is prioritized, creating a dynamic balance between quality and throughput.
Solution Approach 2:
The system enables partial action by allowing doctors to perform preliminary interpretation before the AI analysis is complete. This partial review can identify obviously abnormal cases that require immediate attention, while less urgent cases can wait for full AI analysis, optimizing the overall interpretation throughput without completely sacrificing quality.
3Productivity
If the AI analysis is performed quickly, then the productivity is improved, but the measurement precision of lesion detection may deteriorate
Solution Approach 1:
The system performs preliminary actions by displaying workflow information and estimated completion times before the AI analysis finishes. This allows users to understand the trade-off between speed and precision at each stage and make informed decisions about whether to wait for complete analysis or proceed with preliminary assessment.
Solution Approach 2:
The system implements feedback mechanisms that provide real-time information about analysis progress and quality metrics. This feedback allows users to monitor whether the quick analysis is achieving sufficient precision for their needs, enabling them to adjust their workflow accordingly.
4Device complexity
If the system provides only 'not arrived' status information, then the device complexity is reduced, but the loss of information increases
Solution Approach 1:
The system applies segmentation by dividing the AI analysis process into distinct workflow stages and displaying the status of each stage separately. This segmented information presentation provides comprehensive status details without overwhelming the user, maintaining relative simplicity while reducing information loss.
Solution Approach 2:
The system adds another dimension to the status information by including not only the current state but also the workflow progress and estimated completion time. This multi-dimensional information presentation provides richer context without significantly increasing interface complexity.
Data Source
AI summary
A medical information display apparatus includes a hardware processor that obtains a lesion detection process result obtained by a computer performing a lesion detection process on a medical image, and executes a prevention function of preventing user's inappropriate interpretation of the medical image.