MRI Phase Correction for Partial K-Space Artifact Reduction

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Magnetic Resonance Imaging (MRI) systems face challenges in reconstructing images from partially sampled k-space data, leading to truncation artifacts such as blurring and ringing, which degrade image quality and diagnostic value.

Innovation Solution

A method and system for MRI image reconstruction that involves acquiring a first set of partial k-space data, generating a phase-corrected image using a phase correction factor, transforming the phase-corrected image into a second set of partial k-space data, and reconstructing the image using this data and a weighting function.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If partial k-space sampling is used to increase acquisition efficiency, then productivity is improved, but manufacturing precision deteriorates due to truncation artifacts

Engineering Contradiction:

Improveacquisition efficiencyVSAvoidimage quality

Core Design Contradiction:

ProductivityVSManufacturing precision

Solution Approach 1:

The patent applies preliminary phase correction to the partial k-space data before reconstruction. By estimating the phase error from the acquired partial data and correcting it in advance, the method prevents truncation artifacts from degrading image quality, thereby maintaining diagnostic value while using efficient partial sampling

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent modifies the reconstruction process by introducing phase correction as an additional processing step. This changes the parameters of the reconstruction algorithm to account for phase errors introduced by partial sampling, transforming the raw partial k-space data into artifact-reduced images

Inventive Principle:

Principle #35Parameter changes

2Loss of time

If partial k-space sampling is used to reduce scan time, then loss of time is reduced, but measurement precision deteriorates due to artifacts

Engineering Contradiction:

Improvescan timeVSAvoidimage accuracy

Core Design Contradiction:

Loss of timeVSMeasurement precision

Solution Approach 1:

Phase correction is applied preliminarily to compensate for artifacts before final image reconstruction. This pre-correction step ensures that the reduced scan time does not compromise diagnostic accuracy by eliminating the primary source of reconstruction artifacts

Inventive Principle:

Principle #10Preliminary action

3Device complexity

If conventional reconstruction of partial k-space data is performed, then device complexity is kept simple, but object-generated harmful factors increase due to truncation artifacts

Engineering Contradiction:

Improvereconstruction complexityVSAvoidtruncation artifacts

Core Design Contradiction:

Device complexityVSObject-generated harmful factors

Solution Approach 1:

The patent introduces a preliminary phase correction step that estimates and corrects phase errors before reconstruction. This additional processing step eliminates truncation artifacts while maintaining relative simplicity in the overall reconstruction workflow

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The phase correction factor acts as an intermediary element between the partial k-space data and the final image reconstruction. By introducing this intermediate correction step, the method mediates the harmful effects of partial sampling without requiring complete k-space data

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS12201412B2System and method for reconstruction using a high-resolution phase in magnetic resonance images

Publication Date: 2025.01.21 GE PRECISION HEALTHCARE LLC

AI summary

A method for producing an image of a subject with a magnetic resonance imaging (MRI) comprises acquiring a first set of partial k-space data from the subject and generating a phase corrected image based on a phase correction factor and the first set of the partial k-space data. The method further includes transforming the phase corrected image into a second set of partial k-space data and reconstructing the image of the subject from the second set of the partial k-space data and a weighting function.