Arterial Input Function Selection via Interactive MRI GUI
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Solution Overview
Problem
Current methods for selecting an Arterial Input Function (AIF) in MRI systems are time-consuming and rely solely on mathematical characteristics, lacking consideration for anatomical and physiological knowledge, which hinders the accurate calculation of hemodynamic parameters.
Innovation Solution
A graphical user interface is developed to display MRI images alongside annotated time-course graphs, allowing users to interactively select AIFs based on anatomical knowledge, with features like panning, zooming, and curve-fitting parameters to assist in identifying suitable AIFs for calculating hemodynamic parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automatic methods are used to select AIF based on mathematical characteristics, then the selection process is automated, but the accuracy and reliability of AIF selection deteriorates due to lack of anatomical and physiological knowledge integration
Solution Approach 1:
The patent introduces an intermediary tool - a graphical user interface with curve-fitting analysis - that bridges automatic mathematical processing and expert anatomical knowledge. The system automatically generates and displays multiple candidate AIFs with fitted curves, allowing reviewers to select the appropriate AIF based on both mathematical characteristics and anatomical knowledge, thus resolving the contradiction between automation and reliability.
2Reliability
If manual review and selection of AIF is performed by skilled reviewers, then anatomical and physiological knowledge is integrated, but the time consumption and complexity of the process increases
Solution Approach 1:
The system performs preliminary automatic processing by generating multiple candidate AIFs and displaying them with curve-fitting analysis before the reviewer makes the final selection. This preliminary action reduces the time required for manual review by pre-processing and organizing the data, allowing reviewers to focus only on the final selection based on anatomical knowledge rather than examining raw data from scratch.
Solution Approach 2:
The patent segments the AIF selection process into distinct stages: automatic generation of candidate AIFs, display with curve-fitting analysis, and final reviewer selection. This segmentation allows the system to handle time-consuming computational tasks automatically while reserving expert judgment for the critical decision-making stage, thus reducing overall time loss while maintaining accuracy.
3Measurement precision
If multiple iterations are performed to identify appropriate AIFs, then the accuracy of hemodynamic parameter calculation is improved, but the productivity and efficiency of the study decreases
Solution Approach 1:
The system performs preliminary analysis by automatically generating and displaying multiple candidate AIFs with curve-fitting characteristics before the reviewer makes a selection. This preliminary action reduces the need for multiple iterative selections by providing well-preprocessed candidate options, thus improving productivity while maintaining the precision needed for accurate hemodynamic parameter calculation.
Data Source
AI summary
A graphical user interface and method allows a user to interactively select an arterial input function. An anatomical image and time-course data corresponding to a selected region of interest are displayed simultaneously. The time-course data is displayed as an array of graphs, annotated with best-fit curves and parameters derived from fitting the time-course data. The region displayed in the graphs may be updated by panning and zooming with a mouse in the image. Time-course data corresponding to a graph is selected for use in deriving an arterial input function. The arterial input function is used to calculate maps of hemodynamic parameters.