MRI Super-Resolution via Rectangular K-Space Extraction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing super-resolution methods for magnetic resonance imaging (MRI) cannot be applied to non-rectangular or non-Cartesian k-space acquisitions due to the generation of ringing artifacts and zero-valued areas, leading to deteriorated image quality.
Innovation Solution
A method and interpolator that extracts a completely scanned rectangular portion of non-rectangular k-space data, applies super-resolution in image space, and reintroduces original data to k-space to generate consistent high-resolution raw data, thereby avoiding artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If super-resolution methods are applied to non-rectangular k-space acquisitions, then image resolution is improved, but ringing artifacts and zero-valued areas are generated leading to deteriorated image quality
Solution Approach 1:
The patent segments the non-rectangular k-space data by extracting only the completely scanned rectangular portion, separating it from the non-rectangular acquisition data. This segmentation allows the super-resolution method to process only the valid rectangular data, avoiding the generation of ringing artifacts while still achieving resolution improvement.
Solution Approach 2:
The patent extracts the rectangular portion from the non-rectangular k-space data using extraction means. By taking out only the completely scanned rectangular region and discarding the non-rectangular portions, the method eliminates the source of artifacts while preserving the useful data for super-resolution processing.
2Measurement precision
If rectangular portion of k-space data is extracted and super-resolution is applied, then image resolution is increased, but data consistency must be maintained
Solution Approach 1:
The patent introduces an intermediary process where the extracted rectangular k-space data is transformed to image space, super-resolution is applied, and then the result is transformed back to k-space. This intermediary transformation process maintains data consistency while achieving resolution enhancement.
Solution Approach 2:
The patent implements a feedback mechanism where the super-resolution enhanced image is transformed back to k-space and compared with the original extracted rectangular data. This feedback loop ensures data consistency is maintained while achieving the desired resolution improvement.
Data Source
AI summary
A method and associated interpolation device is described for increasing the resolution of magnetic resonance (MR) image data of an examination object based on MR raw data acquired using a non-rectangular acquisition scheme. The method may include extracting a rectangular portion of the acquired MR raw data, transforming the extracted rectangular portion into image data space, generating high resolution image data based on the image data, transforming the high resolution image data into k-space, partly replacing the high resolution raw data by original raw data assigned to the non-rectangular portion, and transforming the consistent high resolution raw data into image data space.