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Dynamic range compression in MRI by means of a nonlinear gradient pulse
V J Wedeen1, Y S Chao, J L Ackerman
1Department of Radiology, Massachusetts General Hospital, Boston 02114.
Magnetic Resonance in Medicine
|March 1, 1988
Summary
Researchers propose a method to reduce magnetic resonance imaging (MRI) data dynamic range by applying nonlinear gradient pulses. This technique smooths the spin echo, diminishing its peak amplitude and making more information accessible for analog-to-digital converters (ADCs).
Area of Science:
- Medical Imaging
- Physics
- Engineering
Background:
- Magnetic Resonance Imaging (MRI) systems face limitations due to the dynamic range of Nuclear Magnetic Resonance (NMR) signals exceeding analog-to-digital converter (ADC) capabilities.
- High-intensity data points near the spin echo center contribute significantly to the dynamic range, often necessitating the discarding of valuable information.
Purpose of the Study:
- To investigate the feasibility of reducing the dynamic range of MRI spin echoes.
- To enhance the information captured by ADC hardware in MRI by mitigating signal intensity variations.
Main Methods:
- Introduction of an identical nonlinear gradient pulse into each repetition of the MRI imaging pulse sequence before data sampling.
- Modification of the proton phase distribution from a linear to a nonlinear function of image coordinates.
Main Results:
- The nonlinear phase distribution results in a smoothed spin-echo peak, eliminating a single echo center where all protons are in phase.
- This smoothing significantly diminishes the maximum amplitude and dynamic range of the spin echo.
- An order-of-magnitude reduction in maximum echo amplitude and dynamic range is estimated using gradient pulses with quadratic spatial variation.
Conclusions:
- The proposed method effectively reduces the dynamic range of MRI spin echoes.
- This reduction allows for better utilization of ADC hardware, potentially enabling the capture of more detailed information.
- The technique offers a promising approach to overcome current limitations in MRI data acquisition.