MRI Image Processing Combining Axial Diffusion Data
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Solution Overview
Problem
Magnetic Resonance Imaging (MRI) techniques face challenges in obtaining high-quality diffusion weighted images with larger b-factors, as increasing the b-factor can lower the signal-to-noise ratio (SNR) and introduce motion artifacts, and existing computed DWI methods may not accurately combine images from different axial directions.
Innovation Solution
An image processing apparatus that obtains MR images corresponding to different b-factors in various axial directions and calculates computed diffusion weighted images using these images, allowing for the combination of images from different axial directions to enhance image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the application time period of MPG pulse is increased to increase the b-factor, then the diffusion movement reflection in the image is improved, but the signal-to-noise ratio is lowered and motion artifacts increase
Solution Approach 1:
The patent creates computed diffusion weighted images by calculating and synthesizing image data from multiple axial directions. Instead of directly acquiring high b-factor images that suffer from noise and artifacts, the system generates a computational copy of the desired diffusion-weighted image through mathematical processing of lower b-factor images acquired in different directions, thereby achieving high diffusion reflection without the associated noise and motion artifacts.
2Measurement precision
If the application time period of MPG pulse is increased to increase the b-factor, then the diffusion movement reflection in the image is improved, but motion artifacts increase
Solution Approach 1:
The patent generates computed diffusion weighted images by calculating image data from multiple axial directions and synthesizing them. This computational approach creates a replica of the desired high b-factor image without requiring actual long-duration MPG pulse applications, thereby achieving accurate diffusion movement reflection while eliminating the motion artifacts that would otherwise be generated during extended scanning.
3Reliability
If computed DWI is used to obtain DWI-derived image with larger b-factor through calculation, then the image quality is improved, but the precision of combining images from different axial directions is insufficient
Solution Approach 1:
The patent segments the image acquisition process into multiple axial directions (first axial direction, second axial direction, third axial direction). By dividing the overall diffusion-weighted imaging into separate directional components and independently calculating the diffusion weighted image for each direction, the system maintains measurement precision while improving the accuracy of the final combined image through systematic integration of segmented directional data.
Solution Approach 2:
The patent transitions from single-direction image acquisition to multi-dimensional acquisition by obtaining diffusion weighted images from multiple axial directions. This dimensional expansion allows for more comprehensive sampling of diffusion information in three-dimensional space, thereby improving the precision of Apparent Diffusion Coefficient calculations when the images are combined through the calculating process.
Data Source
AI summary
An image processing apparatus according to an embodiment includes processing circuitry. The processing circuitry obtains a first Magnetic Resonance (MR) image corresponding to a first b-factor and corresponding to each of a plurality of axial directions and to obtain a second MR image corresponding to a second b-factor different from the first b-factor and corresponding to each of the plurality of axial directions. The processing circuitry obtains through a calculation, with respect to each of the axial directions, an MR image as a computed image corresponding to a third b-factor different from the first b-factor and the second b-factor by using the first MR image and the second MR image. The processing circuitry generates a combined image by combining together the plurality of computed images each of which was obtained with respect to a different one of the axial directions.