MRI Gradient Pulse Optimization for Noise Reduction
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Solution Overview
Problem
Magnetic resonance sequences in MRI systems face challenges in optimizing gradient pulses for noise reduction and maintaining image quality, with existing methods often resulting in high noise levels, energy consumption, and helium boil-off due to steep gradient edges and rapid switching.
Innovation Solution
A method for optimizing magnetic resonance sequences by automatically adjusting gradient pulses within modifiable time intervals to maintain a constant first moment, minimizing the first derivative of the gradient shape, thereby reducing noise and energy usage, while keeping fixed point intervals unaltered to ensure precise functionality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If gradient pulses with steep edges and rapid switching are used, then imaging speed and resolution are improved, but noise levels increase and energy consumption rises
Solution Approach 1:
The patent applies dynamics by making the gradient pulse shape adaptive rather than fixed. The system dynamically adjusts the gradient waveform within modifiable time intervals to optimize the balance between imaging speed and noise reduction, allowing the gradient profile to be tailored to specific imaging requirements while maintaining performance
Solution Approach 2:
The patent changes parameters by optimizing gradient pulse characteristics (amplitude, duration, shape) within modifiable time intervals while preserving fixed point time intervals. This parameter optimization reduces noise and energy consumption while maintaining the necessary imaging speed and resolution through careful control of gradient moment constraints
2Speed
If gradient pulses with steep edges are used, then imaging speed is improved, but energy consumption increases
Solution Approach 1:
The system dynamically optimizes gradient pulse waveforms to achieve the necessary imaging speed while minimizing energy consumption. By adjusting gradient shape and duration within modifiable time intervals, the system finds the energy-efficient pathway to achieve the required imaging performance
Solution Approach 2:
The patent optimizes gradient pulse parameters (amplitude, duration, temporal distribution) to reduce energy consumption while maintaining imaging speed. The optimization process adjusts these parameters within constraints to minimize the integral of gradient squared over time, which directly relates to energy consumption in gradient coils
3Speed
If gradient pulses with rapid switching are used, then imaging speed is improved, but helium boil-off increases
Solution Approach 1:
The system dynamically adjusts gradient switching profiles to reduce rapid transitions that cause heating. By smoothing gradient transitions within modifiable time intervals while maintaining imaging speed through optimized timing, the system reduces thermal load on the superconducting magnet and minimizes helium boil-off
Solution Approach 2:
The patent changes gradient pulse parameters to reduce switching rate and edge steepness in ways that maintain imaging speed but reduce power dissipation. This parameter optimization directly addresses the heating issue that leads to helium boil-off while preserving the necessary imaging performance
4Object-generated harmful factors
If gradient pulses are optimized for noise reduction, then noise levels decrease, but image quality may be compromised
Solution Approach 1:
The patent applies local quality by applying different optimization strategies to different parts of the gradient sequence. Fixed point time intervals maintain their original gradient characteristics to ensure image quality, while modifiable time intervals are optimized for noise reduction. This localized approach allows noise reduction without compromising overall image quality
Solution Approach 2:
The system dynamically balances noise reduction and image quality by selectively optimizing gradient pulses in modifiable time intervals while preserving critical gradient features in fixed point intervals. This dynamic approach ensures that noise reduction does not come at the expense of image quality
Data Source
AI summary
In a method for optimizing a magnetic resonance sequence of a magnetic resonance apparatus, a magnetic resonance sequence is provided to a computer, the sequence having a number of fixed point time intervals that are to be left unmodified, and a number of modifiable time intervals which may be optimized. The magnetic resonance sequence is automatically analyzed in the computer in order to identify the fixed point time intervals and the modifiable time intervals in the magnetic resonance sequence. At least one gradient pulse, which occurs during at least one modifiable time interval of the number of modifiable time intervals, is optimized by taking the first moment of this at least one gradient pulse into account.