Cardiac MRI Mis-Trigger Detection via ECG Interval Analysis
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Solution Overview
Problem
Existing cardiac MRI methods struggle to accurately identify and exclude MR images acquired with incorrect trigger events, particularly due to cardiac motion variations and mis-triggering, which complicates motion compensation and perfusion analysis.
Innovation Solution
A method to identify MR images acquired with incorrect trigger events by analyzing the series of time differences between acquisitions, using a default time difference and clustering to detect pairs of incorrect time differences, allowing for the exclusion of affected data before reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high acceleration factors are used to increase image resolution and morphologic coverage, then image quality and coverage are improved, but the complexity of reconstruction frameworks increases and motion artifacts worsen
Solution Approach 1:
The patent applies preliminary action by detecting and removing mis-triggered frames before the reconstruction process. The method analyzes ECG trigger intervals to identify incorrect triggers and excludes corresponding frames from the dynamic series prior to reconstruction, preventing motion artifacts from degrading image quality while maintaining the benefits of high acceleration factors
2Ease of manufacture
If regularization methods are used to handle high acceleration factors, then image reconstruction is improved, but performance deteriorates in the presence of motion
Solution Approach 1:
The patent applies preliminary anti-action by proactively identifying and removing mis-triggered frames that would cause motion artifacts before reconstruction. By detecting abnormal ECG trigger intervals and excluding corresponding frames in advance, the method prevents the interaction between motion and regularization that degrades performance
3Measurement precision
If mis-triggered frames are excluded based on reconstructed images, then accuracy is improved, but processing time increases and user interaction is required
Solution Approach 1:
The patent applies preliminary action by performing mis-trigger detection based on ECG trigger interval analysis before image reconstruction. The method calculates intervals between consecutive ECG triggers and identifies mis-triggered frames using threshold-based criteria, eliminating the need for time-consuming iterative reconstruction and user interaction
Solution Approach 2:
The patent replaces the mechanical/interactive process of visual inspection and manual frame removal with an automated computational method. The system uses algorithmic analysis of ECG trigger timestamps to automatically identify and exclude mis-triggered frames, substituting human interaction with efficient computational processing
Data Source
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AI summary
The invention relates to a method for processing a plurality of cardiac MR data sets where the plurality of cardiac MR data sets which were acquired over a plurality of cardiac cycles are provided, each cardiac MR data set having a corresponding time stamp at which the corresponding cardiac MR data set was acquired, wherein each of the cardiac MR data sets was acquired based on a trigger event. A series of time differences is determined between the acquisitions of the cardiac MR data sets based on the time stamps, and a default time difference representing the time difference between 2 consecutive cardiac MR data sets is determined which were acquired using correct trigger events. In the time differences, at least one pair of incorrect time differences is determined in the series of time differences, each incorrect time difference representing the time difference between 2 consecutive MR data sets in which at least one MR data set from the 2 consecutive MR data sets was acquired using an incorrect trigger event. Approved MR data sets are determined comprising only cardiac MR data sets from the plurality of cardiac MR data sets which were acquired using the correct trigger event, based on the at least one pair of incorrect time differences and the approved MR data sets are further processed.