Nonlinear Inverse Reconstruction for MRI Temporal Resolution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current MRI techniques face challenges in achieving real-time imaging with high temporal resolution due to long acquisition times and sensitivity to off-resonance artifacts, geometric distortions, and compromised signal-to-noise ratio, especially when monitoring dynamic processes.
Innovation Solution
A method for reconstructing MR images using a nonlinear inverse reconstruction process that simultaneously estimates coil sensitivities and image content, combined with a gradient-echo sequence and non-Cartesian k-space trajectories, allowing for rapid and continuous imaging with enhanced undersampling factors and improved image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If high-speed acquisition techniques such as single-shot gradient-echo sequences are used, then acquisition time is reduced, but geometric distortions and local signal losses occur due to sensitivity to off-resonance effects
Solution Approach 1:
The patent changes the k-space sampling parameters from Cartesian to radial trajectories, and from full sampling to undersampled sampling. This allows reducing the number of sampling points while maintaining image quality, thereby reducing acquisition time without sacrificing reliability
Solution Approach 2:
The patent uses compressed sensing theory to create a compressed representation of k-space data through radial sampling. By exploiting the sparsity of image content in certain domains, the method reconstructs high-quality images from highly undersampled data, achieving both fast acquisition and reliable reconstruction
2Reliability
If single-shot MRI sequences employing radiofrequency-refocused spin echoes are used, then geometric distortions are avoided, but radiofrequency power absorption increases causing local tissue heating
Solution Approach 1:
The patent changes the pulse sequence parameters by using gradient-echo sequences with radial k-space sampling instead of spin-echo sequences. This parameter change maintains the advantage of avoiding geometric distortions while significantly reducing radiofrequency power absorption and tissue heating through the use of lower flip angles and optimized pulse timing
3Adaptability or versatility
If radial encoding schemes are used, then continuous monitoring of moving objects is improved, but acquisition time for images with reasonable spatial resolution remains long
Solution Approach 1:
The patent applies partial sampling by using radial k-space trajectories with undersampling factors of 2-4. Instead of acquiring all k-space data points, the method strategically samples only the necessary radial lines, reducing acquisition time while maintaining sufficient information content for high-quality image reconstruction through compressed sensing algorithms
4Loss of time
If sliding window method with gridding is used, then temporal resolution of about 50 ms can be obtained, but image quality deteriorates due to rectilinear interpolation artifacts
Solution Approach 1:
The patent replaces the gridding approximation method with direct inverse Fourier transformation of radially sampled k-space data. Instead of using rectilinear interpolation to estimate missing k-space points, the method uses compressed sensing algorithms to directly reconstruct images from undersampled radial data, eliminating interpolation artifacts while maintaining fast temporal resolution
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 significantly reduces acquisition times, achieves high-quality images with a frame rate of up to 50 frames per second, and is robust to motion and artifacts, enabling real-time MRI with improved temporal and spatial resolution.
Implementation Method 1
magnetic resonance imaging (MRI)
Implementation Method 2
spatially encodes an MRI signal received with the at least one radiofrequency receiver coil using a non-Cartesian k-space trajectory
Implementation Method 3
subjecting the sets of image raw data to a nonlinear inverse reconstruction process to provide the sequence of MR images, wherein each is created by a simultaneous estimation of a sensitivity of the at least one receiver coil and the image content
Data Source
AI summary
A method for reconstructing a sequence of magnetic resonance (MR) images of an object under investigation, includes the steps of (a) providing a series of sets of image raw data including an image content of the MR images to be reconstructed, the image raw data being collected with the use of at least one radiofrequency receiver coil of a magnetic resonance imaging (MRI) device, wherein each set of image raw data includes a plurality of data samples being generated with a gradient-echo sequence, in particular a FLASH sequence, that spatially encodes an MRI signal received with the at least one radiofrequency receiver coil using a non-Cartesian k-space trajectory, each set of image raw data includes a set of homogeneously distributed lines in k-space with equivalent spatial frequency content, the lines of each set of image raw data cross the center of k-space and cover a continuous range of spatial frequencies, and the positions of the lines of each set of image raw data differ in successive sets of image raw data, and (b) subjecting the sets of image raw data to a regularized nonlinear inverse reconstruction process to provide the sequence of MR images, wherein each of the MR images is created by a simultaneous estimation of a sensitivity of the at least one receiver coil and the image content and in dependency on a difference between a current estimation of the sensitivity of the at least one receiver coil and the image content and a preceding estimation of the sensitivity of the at least one receiver coil and the image content.