MRI Super-Resolution Using ROI-Reduced Oversampled K-Space
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Solution Overview
Problem
Conventional super-resolution methods in magnetic resonance imaging (MRI) are time-consuming due to processing large oversampled fields of view, leading to prolonged reconstruction times without adequately addressing image quality issues.
Innovation Solution
The method involves oversampling k-space data in the phase-encoding direction, reducing the image region in that direction, and applying a super-resolution algorithm to the reduced data, followed by format adjustments to maintain image quality and reduce processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If super-resolution algorithms are applied to oversampled fields of view to increase image resolution, then image quality is improved, but reconstruction time increases significantly
Solution Approach 1:
The patent divides the oversampled field of view into a region of interest (ROI) and surrounding areas. The super-resolution algorithm is applied only to the ROI portion rather than the entire oversampled field, thereby maintaining high image resolution for the important region while significantly reducing the computational burden and reconstruction time.
Solution Approach 2:
The patent extracts and processes only the essential portion (region of interest) from the complete oversampled data. By isolating and applying super-resolution specifically to the ROI, the method eliminates unnecessary processing of non-critical areas, achieving a balance between image quality and processing efficiency.
2Productivity
If k-space data is partially sampled to reduce acquisition time, then scanning efficiency is improved, but image resolution deteriorates
Solution Approach 1:
The patent applies super-resolution processing as a preliminary enhancement step to the partially sampled k-space data before final image reconstruction. This preliminary action compensates for the resolution loss caused by partial sampling, allowing efficient scanning with acceptable acquisition time while restoring high image resolution through algorithmic enhancement.
Data Source
AI summary
A method for generating magnetic resonance image data of an object under examination with increased resolution is described. In the method, oversampled k-space data is received from a region of interest of the object under examination, wherein the oversampled k-space data is obtained by oversampling in the phase-encoding direction with a predetermined oversampling factor greater than 1. Magnetic resonance image data is reconstructed based on the sampled k-space data, with an image region that is enlarged by the oversampling factor relative to the region of interest. In addition, reduced magnetic resonance image data is generated by reducing the size of the enlarged image region in the phase-encoding direction. Finally, image data with increased resolution is generated by applying a super-resolution method to the reduced magnetic resonance image data. An image data generating device is also described. In addition, a magnetic resonance imaging system is described.