Perfusion Imaging Protocol Selection via Plausibility Check
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Solution Overview
Problem
Computed tomography perfusion (CTP) imaging requires significant user interaction for generating perfusion maps, making the process time-consuming and error-prone, while automation can lead to incorrect diagnoses and therapeutic decisions due to lack of patient-specific parameters and interaction.
Innovation Solution
A method of computer-assisted analysis that selects a processing protocol from an electronic repository based on perfusion and non-imaging data, allowing for automatic or semi-automated processing with a plausibility check to adjust the protocol and interaction mode, ensuring accurate and efficient generation of perfusion maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If user interaction is increased to ensure accurate processing, then diagnostic accuracy is improved, but processing time and complexity increase
Solution Approach 1:
The system dynamically adjusts the degree of automation based on data quality assessment. The plausibility checker evaluates processed data and automatically switches between fully automated mode and interactive mode, making the processing mode flexible rather than fixed, thus resolving the contradiction between speed and accuracy
Solution Approach 2:
The plausibility check mechanism provides feedback on data quality and processing results. When data quality is sufficient, the system maintains automated processing; when quality is insufficient, the system triggers interactive review, creating a feedback loop that balances speed and accuracy
2Productivity
If full automation is implemented to reduce user interaction, then processing speed is improved, but reliability decreases due to potential errors
Solution Approach 1:
The system performs self-assessment through the plausibility checker, which automatically evaluates whether processed data meets quality standards. This self-service mechanism allows the system to autonomously determine when automated processing is sufficient and when human intervention is needed, maintaining both speed and reliability
Solution Approach 2:
The plausibility checker acts as an intermediary between automated processing and final diagnostic output. It serves as a quality gate that can trigger interactive review when needed, mediating between the efficiency of automation and the reliability of human expertise
3Measurement precision
If interactive processing mode is used to ensure data quality, then processing accuracy is improved, but ease of operation deteriorates due to complex user tasks
Solution Approach 1:
The processing workflow is segmented into distinct phases: automated processing phase and interactive review phase. The plausibility checker determines which phase is needed based on data quality, breaking down the complex decision-making into manageable segments that reduce user burden while maintaining quality
Data Source
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AI summary
A method includes executing, via a data analyzer (122), computer executable instructions that select, without user interaction, a processing protocol (212) from an electronic repository (210) of protocols based on imaging data and non-imaging data corresponding to the patient, processing, via the data analyzer (122), functional imaging data for a subject with the selected processing protocol (212) under a first processing mode, and performing a plausibility check on the processed data.