Rotational Imaging Artifact Management via Seam Line Alignment

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Solution Overview

Problem

Intravascular imaging systems face challenges with seam line and guidewire shadow artifacts, which are not effectively minimized by existing methods, leading to discontinuities in data acquisition and image quality.

Innovation Solution

The method involves orienting the seam line artifact to overlap with the guidewire shadow artifact, ensuring both are positioned at a common rotational position within a three-dimensional dataset, thereby reducing the impact of these artifacts to a single gap in the image, improving visualization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Object-affected harmful factors

If the pitch of the helix is kept tight to minimize seam line artifact, then the appearance of seam line is reduced, but the guidewire artifact remains unaffected and image completeness is compromised

Engineering Contradiction:
Improveseam line artifactVSAvoidimage completeness
Core Design Contradiction:
Object-affected harmful factorsVSLoss of information

Solution Approach 1:

The patent transforms the problem from a two-dimensional display artifact issue to a three-dimensional spatial registration problem. By rotating the seam line artifact to align with the guidewire shadow artifact in the angular dimension, both artifacts are consolidated into a single location, effectively reducing their combined impact while preserving complete volumetric data acquisition.

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

Solution Approach 2:

The patent merges two separate artifacts (seam line and guidewire shadow) into a single consolidated artifact location by rotational alignment. This combining approach reduces the total artifact burden from two separate discontinuities to one unified gap, improving overall image interpretability without sacrificing data completeness.

Inventive Principle:
Principle #5Merging (Combining)

2Object-affected harmful factors

If traditional artifact minimization methods are used, then seam line artifact is partially reduced, but multiple separate artifacts remain in the image

Engineering Contradiction:
Improveartifact reductionVSAvoidimage processing complexity
Core Design Contradiction:
Object-affected harmful factorsVSDevice complexity

Solution Approach 1:

The patent changes the angular parameter of the seam line artifact through rotational transformation. By adjusting the orientation angle of the seam line to match the guidewire shadow's angular position, the system consolidates artifacts without requiring complex spatial reconstruction or data re-acquisition, maintaining procedural simplicity while achieving superior artifact management.

Inventive Principle:
Principle #35Parameter changes

3Manufacturing precision

If the beam longitudinal displacement is reduced, then seam line artifact is minimized, but guidewire shadow artifact persists independently

Engineering Contradiction:
Improvedata continuityVSAvoidguidewire shadow
Core Design Contradiction:
Manufacturing precisionVSObject-generated harmful factors

Solution Approach 1:

Instead of trying to eliminate the guidewire shadow artifact by adjusting beam parameters, the patent inverts the approach by rotating the seam line artifact to align with the guidewire shadow. This reverse strategy accepts the guidewire shadow as an unavoidable feature and strategically positions the seam line artifact to coincide with it, thereby reducing the total number of discontinuities.

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

Data Source

PatentEP2661721B1Artifact management in rotational imaging
Publication Date: 2018.02.21 PHILIPS IMAGE GUIDED THERAPY CORP
  • EP2661721B1 patent drawingFigure 1~2
  • EP2661721B1 patent drawingFigure 3~4
  • EP2661721B1 patent drawingFigure 5~6

AI summary

A method for artifact management in a rotational imaging system is presented. The method includes the steps of acquiring data employing a helical scanning pattern over N revolutions, where N is greater than 1, and detecting at least one artifact in the acquired data of each revolution. The method further includes segmenting the data acquired over N revolutions into N- 1 data frames each bounded by at least one of the at least one artifacts.