CT Density Measurement With Diffraction Artifact Correction
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Solution Overview
Problem
Existing methods are inadequate for accurately measuring the true density of materials with microscopic features, such as powders and composite particles, due to challenges in constructing appropriate density standards and mitigating X-ray imaging artifacts like Fresnel diffraction and beam hardening.
Innovation Solution
A computer-implemented method using CT imaging with diffraction artifact correction, involving segmentation of imaging data, deconvolution of histograms, and construction of an intensity-density calibration curve, utilizing a calibrant with known densities to determine the density of materials with microscopic features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional density measurement methods (mass-volume measurement, density gradient columns, gas pycnometry) are used, then measurement simplicity or direct measurement capability is improved, but measurement precision deteriorates for materials with microscopic features due to inability to capture true density of powders, composite particles, and porous materials
Solution Approach 1:
The patent replaces conventional mechanical density measurement methods (mass-volume measurement, density gradient columns, gas pycnometry) with X-ray imaging-based measurement. This substitution enables non-contact, non-destructive measurement of true density for microscopic materials by capturing X-ray attenuation signals and processing them through specialized algorithms, thereby achieving both ease of measurement and high precision for powders, composite particles, and porous materials.
Solution Approach 2:
The patent changes the measurement parameter from macroscopic bulk properties to microscopic X-ray attenuation characteristics. By measuring X-ray attenuation at the pixel level and correlating it with electron density, the method captures true density information of microscopic features that conventional methods miss, achieving high measurement precision for materials with complex microstructures.
2Measurement precision
If X-ray imaging is used for density measurement, then measurement capability for microscopic features is improved, but measurement precision deteriorates due to diffraction artifacts (Fresnel diffraction) and beam hardening effects
Solution Approach 1:
The patent converts harmful diffraction artifacts into useful information by developing algorithms that recognize and process the characteristic intensity patterns caused by Fresnel diffraction. Instead of simply removing these artifacts, the method utilizes the structured nature of diffraction patterns to infer true material density, thereby transforming a measurement obstacle into a diagnostic tool for characterizing microscopic materials.
Solution Approach 2:
The patent introduces computational algorithms as an intermediary between X-ray imaging and density measurement. These algorithms act as a mediator that processes raw X-ray images, separates true density information from artifact-induced intensity variations, and produces accurate density measurements. The intermediary processing step enables the system to achieve high measurement precision despite the presence of X-ray imaging artifacts.
3Measurement precision
If appropriate density standards are constructed for calibration, then measurement accuracy is improved, but device complexity increases due to difficulty in constructing standards for microscopic materials
Solution Approach 1:
The patent uses computational modeling to create virtual density standards that replicate the X-ray attenuation characteristics of materials with known densities. Instead of physically constructing calibration standards for each microscopic material type, the method generates synthetic reference data through simulation, thereby simplifying the calibration process while maintaining measurement accuracy for diverse microscopic materials.
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
Enables accurate determination of true density of materials with microscopic features by correcting for diffraction artifacts, providing precise density measurements and uncertainty analysis.
Implementation Method 1
Computed Tomography (CT) imaging is an imaging modality that is sensitive to the true density of an imaged object due to the source signal transmitting through the entire object
Implementation Method 2
X-ray imaging artifacts such as Fresnel diffraction and beam hardening
Data Source
AI summary
Embodiments determine the density of materials and objects imaged using computed tomography (CT). An embodiment co-images a material of unknown density with a calibrant of known density. The digitally reconstructed CT images are segmented into the unknown material phase and the known material phases of the calibrant. Image intensity histograms of the unknown material are obtained. Using the known calibrant densities, an intensity-density mapping is calculated to determine the unknown material density based on its measured CT intensity. The method described herein utilizes a novel deconvolution of the intensity histograms to correct for CT imaging artifacts that impact the material phase intensities. The density of micronized materials and features such as particles, microspheres, porosity, and multiphase composites which are difficult to measure with conventional techniques can be measured using the embodiments. The design of custom sample holders for co-imaging a material with the calibrant and uncertainty estimation are also described.