Projection-Based Spectral X-Ray Imaging Material Weighting
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Solution Overview
Problem
Existing X-ray imaging systems, particularly CT imaging systems, face challenges in achieving improved image quality in terms of reduced noise, increased contrast-to-noise ratio (CNR), and enhanced patient dose efficiency without compromising image quality.
Innovation Solution
The proposed method involves performing projection-based material decomposition on spectral X-ray data to generate material basis sinograms, followed by a weighted combination of these sinograms to reconstruct images using adaptive material weighting in the projection domain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional X-ray imaging is used, then the system is simple and easy to operate, but image quality in terms of noise reduction and CNR enhancement is insufficient
Solution Approach 1:
The patent applies parameter changes by performing material decomposition in the projection domain using spectral X-ray data, transforming the imaging approach from conventional single-energy to multi-energy spectral imaging. This enables improved image quality through noise reduction and CNR enhancement while maintaining system operation through automated processing algorithms
2Measurement precision
If spectral X-ray imaging with material decomposition is implemented, then image quality and CNR are improved, but additional calibrations and processing complexity are required
Solution Approach 1:
The system performs self-service through automated processing where the image processing system automatically executes material decomposition and weighted combination of material basis sinograms without requiring manual calibration interventions during operation, thereby maintaining ease of operation despite implementing advanced spectral imaging
3Measurement precision
If weighted combination of material basis sinograms is performed, then noise is reduced and image quality is enhanced, but processing time and computational complexity increase
Solution Approach 1:
The patent applies preliminary action by performing material decomposition and generating material basis sinograms in the projection domain before image reconstruction. This preprocessing approach enables efficient noise reduction through weighted combination while optimizing processing time by preparing data in advance for the reconstruction step
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
This approach results in improved image quality with increased CNR, reduced noise, and enhanced patient dose efficiency, while also requiring no additional calibrations during use.
Implementation Method 1
The X-ray source emits X-rays, which pass through a subject or object being imaged and received by the X-ray detector. The emitted X-rays are attenuated by the subject or object as they pass through, and the resulting transmitted X-rays are measured by the X-ray detector.
Implementation Method 2
An example of such a detector is a multi-bin photon counting detector, where each registered photon generates a current pulse which is compared to a set of thresholds, thereby counting the number of photons incident in each of a number of energy bins.
Data Source
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AI summary
There is provided a method (100) for projection-based spectral X-ray imaging, the method comprising performing (110) projection-based material decomposition based on spectral X-ray data to generate a set of material basis sinograms, and performing (120) a weighted combination of at least part of at least two material basis sinograms of the set of material basis sinograms into a reconstructed image based on material weighting in the projection domain.