Magnetic Resonance Image Aliasing Artifact Elimination

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

Solution Overview

Problem

Magnetic resonance images often suffer from aliasing artifacts due to phase encoding, which can lead to incorrect diagnoses by obscuring anatomical details and requiring longer acquisition and processing times.

Innovation Solution

A method that compares and processes two magnetic resonance images acquired with phase encoding for columns and rows, adjusting numerical values based on differences to construct a new matrix structure that minimizes artifacts, thereby improving image definition and reducing noise.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If phase encoding is used to examine a determined region in detail, then the definition of the anatomical part of interest is improved, but aliasing artifacts are produced that compromise the examination results

Engineering Contradiction:
Improvedefinition of anatomical partVSAvoidaliasing artifacts
Core Design Contradiction:
Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The image is divided into multiple regions based on intensity thresholds, allowing different processing to be applied to different parts of the image. This segmentation enables the preservation of detailed anatomical regions while identifying and removing aliasing artifacts in other areas.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

Instead of trying to prevent aliasing artifacts during image acquisition, the method inverts the approach by acquiring the image with phase encoding and then removing artifacts through post-processing. The artifact removal is achieved by comparing pixel intensities and identifying regions that deviate from expected anatomical patterns.

Inventive Principle:
Principle #13The other way round (Inversion)

2Measurement precision

If the field of view is reduced to focus on a determined region, then the examination detail is improved, but aliasing artifacts from surrounding areas are introduced

Engineering Contradiction:
Improveexamination detailVSAvoidaliasing artifacts from surrounding areas
Core Design Contradiction:
Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

Different quality processing is applied to different regions of the image. Regions of interest with anatomical structures are preserved with high detail, while regions containing only aliasing artifacts are identified and removed. This local quality approach maintains examination detail where needed while eliminating artifacts elsewhere.

Inventive Principle:
Principle #3Local quality

3Measurement precision

If image processing is performed to remove artifacts, then the diagnostic accuracy is improved, but the processing time is increased

Engineering Contradiction:
Improvediagnostic accuracyVSAvoidprocessing time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

Rather than processing the entire image uniformly, the method applies processing only to regions where artifacts are detected. By using intensity thresholding and region identification, the processing is limited to necessary areas, reducing overall processing time while maintaining diagnostic accuracy in critical regions.

Inventive Principle:
Principle #16Partial or excessive action

Data Source

PatentEP3740775B1Method for eliminating aliasing artifacts in a magnetic resonance image
Publication Date: 2021.12.15 DELLORSO ANDREA
  • EP3740775B1 patent drawingFigure 1
  • EP3740775B1 patent drawingFigure 2A
  • EP3740775B1 patent drawingFigure 2B

AI summary

Method for eliminating aliasing artifacts in a magnetic resonance image, comprising the steps of obtaining a first and a second starting image (100a,100b) obtained by a determined acquisition sequence and using, respectively a phase encoding for columns, and a phase encoding for rows. Both the first and the second starting image (100a,100b) are organized in according to a matrix structure (m·n) comprising a plurality of portions (101a,101b) arranged according to m rows and n columns, each of which is associated to a respective numerical value corresponding to the light intensity of the portion. The method provides a translation step for translating at least one between the first and the second starting image (100a,100b) with respect to a respective reference system, in such a way to minimize the differences among the numerical values of the homologous portions of the first and of the second starting image due to the fact that the first and the second starting image are obtained by a different encoding phase.