MRI Signal Representation Determination via Joint Dimension Processing
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Solution Overview
Problem
Current MRI systems are inefficient and inaccurate in determining signal representations and quantitative parameters of subjects, as they rely on conventional methods that independently process echo signals from different coil units, leading to suboptimal combination and analysis of data.
Innovation Solution
A system and method that acquire and process a plurality of signals from an MRI device, identifying a primary and secondary signal dimension to determine a signal representation by applying an optimization function, which incorporates both dimensions for improved accuracy and efficiency in determining quantitative parameters like T1, T2, and ADC values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to independently process echo signals from different coil units and combine images using SOS or ACC algorithms, then the processing workflow is straightforward and easy to implement, but the determination efficiency is low and the accuracy of quantitative parameters is insufficient
Solution Approach 1:
The patent merges the processing of multiple echo signals from different coil units into a unified signal representation determination process. Instead of independently processing each coil unit's signals and then combining images, the method jointly determines signal representations for all coil units simultaneously, extracting common physiological information while accounting for individual coil characteristics. This integration improves both accuracy and efficiency by eliminating redundant processing steps.
Solution Approach 2:
The patent introduces a new dimension of analysis by determining signal representations that capture physiological characteristics across multiple signal dimensions simultaneously. The approach moves beyond traditional single-parameter analysis by considering multiple echo signals from multiple coil units in a multidimensional space, enabling more accurate characterization of tissue properties through joint processing.
2Measurement precision
If conventional methods independently process each coil unit's echo signals, then the processing approach is simple and computationally less intensive, but the result accuracy is compromised due to suboptimal combination of data
Solution Approach 1:
The patent segments the complex processing task into distinct functional components: individual coil unit signal processing, identification of primary and secondary signal dimensions, determination of preliminary signal representations, and final combination to produce the overall signal representation. This segmentation allows each component to be optimized independently while maintaining overall system manageability and improving accuracy through specialized processing at each stage.
3Productivity
If quantitative parameters are determined based on echo images from different coil units using data fitting algorithms, then the methodology is conventional and well-established, but the determination results are sometimes inaccurate and inefficient
Solution Approach 1:
The patent implements feedback mechanisms by using the determined signal representations to inform and refine the quantitative parameter determination process. The signal representations, which capture physiological characteristics across multiple dimensions, provide feedback that guides the data fitting algorithm to converge more reliably on accurate quantitative parameters. This iterative feedback loop improves both efficiency and reliability compared to conventional single-pass methods.
Data Source
AI summary
A method for determining a signal representation of a subject in MRI is provided. The method may include acquiring a plurality of signals of the subject. The plurality of signals may be generated using an MRI device, and each of the plurality of signals may correspond to a set of values in a plurality of signal dimensions of signal acquisition using the MRI device. The method may include determining, among the plurality of signal dimensions, a primary signal dimension and at least one secondary signal dimension, the primary signal dimension being associated with the signal representation. The method may also include determining the signal representation of the subject based on the primary signal dimension, the at least one secondary signal dimension, and the plurality of signals.