Real-Time Gradient Impulse Response Correction in MRI
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Solution Overview
Problem
Current magnetic resonance imaging (MRI) technologies face challenges in correcting Gradient Impulse Response Functions (GIRF)-induced errors, which result in artifacts and image degradation, especially in real-time data acquisition and during patient movements, as existing methods require offline correction and knowledge of the entire sequence.
Innovation Solution
A method for real-time correction of GIRF-induced errors by dividing the magnetic resonance sequence into event blocks and applying a digital pre-emphasis filter to the target gradient signal, allowing for on-the-fly modification of gradient pulses to match the intended waveform, thereby reducing or eliminating GIRF-induced impairments without requiring changes to the sequence code.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If offline correction methods are used to correct GIRF-induced errors, then measurement precision is improved, but loss of time occurs due to requiring entire sequence knowledge and offline processing
Solution Approach 1:
The patent divides the magnetic resonance sequence into discrete event blocks that can be processed independently in real-time. Each event block contains gradient waveforms and associated metadata that are corrected individually as they are generated, eliminating the need to wait for the entire sequence before applying GIRF corrections.
Solution Approach 2:
The patent applies GIRF corrections preliminarily during the sequence generation phase rather than as a post-processing step. By calculating and applying corrections to gradient waveforms before actual data acquisition begins, the system achieves accurate corrections without requiring offline processing of complete sequences.
2Productivity
If real-time correction is implemented during data acquisition, then productivity is improved by allowing sequence adaptation, but device complexity increases due to continuous processing requirements
Solution Approach 1:
The patent segments the gradient waveform generation and correction processes into discrete, manageable event blocks. This segmentation allows the system to process corrections in small, incremental steps rather than requiring complex continuous processing of entire sequences, reducing computational overhead.
Solution Approach 2:
The system performs self-correction by automatically applying GIRF corrections to gradient waveforms as they are generated, without requiring external intervention or complex post-processing systems. The correction mechanism is integrated into the existing sequence execution pipeline, allowing the system to correct its own gradient errors in real-time.
3Measurement precision
If the entire magnetic resonance sequence is known in advance for correction, then measurement precision is improved, but adaptability deteriorates as real-time sequence modification becomes impossible
Solution Approach 1:
The patent applies corrections preliminarily to each event block as it is generated, rather than requiring knowledge of the entire sequence in advance. This allows the system to maintain high correction accuracy for each segment while simultaneously adapting to real-time requirements and modifying the sequence as needed.
Solution Approach 2:
The patent implements a dynamic correction approach where GIRF corrections are applied continuously to incoming event blocks rather than using a static pre-calculated correction for the entire sequence. This dynamic processing enables real-time adaptation while maintaining correction accuracy for each segment of the sequence.
Data Source
AI summary
In a method and magnetic resonance imaging apparatus having a scanner that for acquires a magnetic resonance dataset, a magnetic resonance sequence is provided to a computer and is converted in the computer into a digital sequence execution signal that includes a target gradient waveform in the form of a time-discrete target gradient signal the computer calculates a pre-GIRF gradient signal by applying a digital pre-emphasis filter to the target gradient signal. The computer transmits the pre-GIRF gradient signal to the magnetic resonance system scanner and) the scanner executes the digital sequence execution signal containing the pre-GIRF gradient signal in order to acquire magnetic resonance raw data.