MRI Resolution Adaptation for SNR and Image Quality
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Solution Overview
Problem
Conventional MRI methods generate calculation images with a fixed resolution for all parameters, leading to decreased image quality and accuracy when high resolution is not necessary for certain parameters, such as B1 distribution, due to a low signal-to-noise ratio (SN ratio).
Innovation Solution
The technology adjusts the resolution of reconstructed images based on the optimal resolution required for each parameter to be estimated, allowing for separate optimal resolution calculations for different parameters, thereby improving image quality and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a fixed high resolution is used for all calculation images, then the resolution requirement for parameters needing high detail (like T1 and T2) is satisfied, but the signal-to-noise ratio decreases for parameters that do not require high resolution (like B1 distribution)
Solution Approach 1:
The patent applies local quality by assigning different resolution levels to different calculation images based on their specific requirements. High-resolution images are generated for parameters like T1 and T2 that require detailed spatial information, while low-resolution images are generated for parameters like B1 distribution that do not benefit from high resolution. This resolves the contradiction by making resolution adaptive to each parameter's needs rather than applying a uniform high resolution to all parameters.
2Ease of operation
If calculation images of multiple parameters are generated simultaneously with fixed resolution, then the processing workflow is simplified, but the image quality and accuracy decrease for parameters with lower optimal resolution requirements
Solution Approach 1:
The patent implements dynamics by making the resolution parameter adaptive rather than fixed. The system dynamically determines the appropriate resolution for each calculation image based on the specific parameter being estimated and its optimal resolution requirements. This allows the processing system to automatically adjust resolution settings for different parameters while maintaining a unified workflow, thus improving image quality without complicating the overall processing procedure.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the image quality and estimation accuracy of calculation images by optimizing the resolution for each parameter, reducing noise and improving the SN ratio, especially for parameters that do not require high resolution.
Implementation Method 1
An MRI apparatus is a medical image diagnosis apparatus that causes a hydrogen nucleus in an arbitrary plane crossing a subject to generate nuclear magnetic resonance
Implementation Method 2
a phase encoding magnetic field gradient and a readout magnetic field gradient in directions orthogonal to each other in a tomographic surface are applied
Data Source
AI summary
A technology of improving image quality of a calculation image or parameter estimation accuracy even in a case where a method of simultaneously generating calculation images of a plurality of parameters is used is provided. Thus, by utilization of a reconstructed image in an optimal resolution of each parameter to be estimated, a value of the parameter is estimated and a calculation image that is a distribution of the value of the parameter is acquired. A reconstructed image in an optimal resolution is acquired by adjustment of a resolution of a reconstructed image acquired in an optimal resolution of an estimation parameter with the highest optimal resolution among parameters to be estimated in scanning. Alternatively, in scanning, only a reconstructed image used for calculation of a predetermined parameter to be estimated is acquired in an optimal resolution of the parameter to be estimated.