Internal MRI Detector for Motion-Corrected High-Resolution Imaging
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Solution Overview
Problem
Current MRI endoscopy systems are limited by slow acquisition speeds, leading to motion artifacts and susceptibility to physiological and random motions, which degrade high-resolution image quality, especially at frame rates below 2 frames per second.
Innovation Solution
The implementation of active internal MRI detectors with spatial encoding projections and error-minimizing algorithms for sparse under-sampling of image k-space, combined with projection shifting to correct motion artifacts and enhance acquisition speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional MRI scan sequences are used, then image quality can be maintained, but acquisition speed is slow (limited to ~2 frames/s) causing motion artifacts
Solution Approach 1:
The patent divides the k-space into multiple segments and uses compressed sensing to selectively sample only the most important segments, rather than uniformly sampling all k-space. This segmentation approach allows faster acquisition by focusing sampling effort on critical frequency components while maintaining image quality.
Solution Approach 2:
The patent applies partial sampling of k-space using compressed sensing algorithms, where instead of fully sampling all frequency components, only a strategic subset is acquired. This partial action reduces scan time while the reconstruction algorithm fills in the missing data to maintain image quality.
2Productivity
If frame rate is increased to reduce motion artifacts, then acquisition speed improves, but signal-to-noise ratio and image quality deteriorate
Solution Approach 1:
The patent incorporates feedback mechanisms where the compressed sensing algorithm iteratively refines the image reconstruction based on the acquired k-space data. This feedback loop allows the system to optimize the balance between sampling density and image quality, maintaining high frame rates while preserving signal-to-noise ratio through intelligent reconstruction.
Solution Approach 2:
The patent dynamically adjusts sampling parameters and reconstruction algorithms based on the specific imaging requirements and acquired data characteristics. By changing parameters such as sampling density, reconstruction method, and regularization strength, the system optimizes both frame rate and image quality for different imaging scenarios.
3Manufacturing precision
If internal MRI detectors are used, then spatial resolution improves, but device complexity increases due to integration challenges
Solution Approach 1:
The patent designs the internal MRI detector system to serve multiple functions: it acts as both the imaging element and the signal reception component. This multi-functionality reduces the number of separate components needed, thereby reducing overall device complexity while maintaining high spatial resolution capabilities.
Solution Approach 2:
The patent integrates the detector elements within the MRI scanner structure in a nested configuration, where the detector is positioned within the magnetic field generation system. This nesting approach allows the detector to utilize the existing magnetic field infrastructure, reducing the need for separate complex field generation components.
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 increases acquisition speed and reduces motion sensitivity, enabling high-resolution real-time internal MRI and endoscopy with frame rates up to 10 frames per second and improved image quality by correcting motion artifacts and retaining high-resolution information.
Implementation Method 1
magnetic resonance imaging involves providing bursts of radio frequency energy on a specimen positioned within a main magnetic field in order to induce responsive emission of magnetic radiation from the hydrogen nuclei or other nuclei
Implementation Method 2
The pixel value may be established in a computer by employing Fourier Transformation (FT) which converts the signal amplitude and phase as a function of time to signal as a function of frequency, which translates to spatial position within the volume
Data Source
AI summary
A method of internal MRI employing at least one active internal MRI detector located within a sample of interest. The method includes applying an MRI pulse sequence to the sample of interest. The MRI pulse sequence includes spatial encoding projections. The method further includes receiving MRI signals at the active internal MRI detector and reconstructing at least one MRI image from the MRI signals using an error minimizing algorithm. The MRI pulse sequence provides an increase in an acquisition speed when reconstructing the at least one MRI image by sparsely under-sampling an image k-space in at least one dimension.