3D Dual-Energy X-Ray Quality Check for Contrast Agent Artifacts
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Solution Overview
Problem
Contrast agent concentration fluctuations during projection data acquisition lead to artifacts in reconstructed 3D CA maps and VNC images, reducing their diagnostic value in coronary CTA imaging.
Innovation Solution
A system and method for image processing that includes segmenting volume images for contrast agent contributions, forward-projecting the segmented images onto spectrally processed projection data, and establishing a quality indicator for concentration changes, allowing assessment and potential corrective actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If spectral imaging is performed with contrast agent during acquisition, then diagnostic information is enhanced, but artifacts occur due to contrast agent concentration fluctuations
Solution Approach 1:
The system performs preliminary segmentation of the volume image to identify contrast agent contributions before reconstruction, and conducts forward-projection to predict expected projection data. This preliminary action allows detection of concentration changes before they cause artifacts, enabling preventive quality assessment
Solution Approach 2:
The system establishes a feedback loop by comparing forward-projected segmented volume data with actual spectrally processed projection data. The quality indicator provides feedback about contrast agent concentration stability, allowing real-time assessment and potential corrective actions to be taken
2Reliability
If contrast agent concentration is monitored for quality assessment, then image quality is improved, but system complexity increases
Solution Approach 1:
The system uses the existing spectral imaging apparatus and reconstruction pipeline for multiple purposes: standard imaging reconstruction and quality assessment based on contrast agent concentration monitoring. The segmentor and forward-projector serve dual functions in both image generation and quality verification
Solution Approach 2:
The system performs self-verification by using its own reconstruction pipeline to generate expected projection data from segmented volume images. The quality indicator is generated internally without requiring external reference measurements, making the system self-sufficient for quality assessment
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system quantifies the quality of reconstructed imagery by identifying artifacts caused by contrast agent concentration changes, enabling real-time assessment and efficient corrective actions to ensure accurate imaging results.
Implementation Method 1
3D dual-energy x-ray imaging
Implementation Method 2
contrasted spectral imagery reconstructions
Data Source
Figure 1~1A
Figure 2
Figure 3
AI summary
System (SYS) and related method for image processing. The system comprises an input interface (IN) for receiving, a volume image reconstructed from spectrally processed projection data acquired by a spectral imaging apparatus (IA) whilst contrast agent is present in a field of view of the spectral imaging apparatus during acquisition. A segmentor (SC) segments the volume image for contrast agent contributions to obtain a segmented volume image. A forward-projector (FP) forward-projects the segmented volume image onto the spectrally processed projection data. A quality checker (QC) establishes quality indicator data indicative of a mismatch between the forward-projected segmented volume image, and the spectrally processed projection data. The output data may be used to assess to what extent the reconstructed data is comprised by artifacts.