Spectral Imaging Object Characterization via Spatial Smoothing
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Solution Overview
Problem
Existing methods for characterizing objects using x-ray or gamma radiation require significant irradiation to determine equivalent thicknesses of materials, which can be harmful and inefficient.
Innovation Solution
A method that involves irradiating an object with ionizing electromagnetic radiation, detecting the transmitted radiation with a pixelated detector, forming energy spectra with multiple energy bands, estimating equivalent thicknesses of basic materials, and calculating structural parameters to characterize the object with reduced irradiation by spatially smoothing and regularizing the thicknesses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional spectral imaging methods are used to determine equivalent thicknesses of materials, then material characterization is achieved, but the radiation exposure to the object is high and harmful
Solution Approach 1:
The patent applies preliminary action by performing spatial smoothing of the attenuation map before the decomposition step. This pre-processing step creates a regularized structural framework that guides the subsequent material decomposition, allowing accurate equivalent thickness determination with fewer photons. The smoothing operation is performed in advance to establish a stable geometric basis that reduces the statistical noise that would otherwise require higher radiation doses to overcome.
Solution Approach 2:
The patent replaces the conventional direct decomposition approach with an iterative optimization method that substitutes traditional algebraic reconstruction with a regularization-based solution. By using an iterative algorithm that incorporates spatial smoothing constraints, the system achieves equivalent thickness measurement without requiring the high photon flux that conventional methods demand, thereby reducing radiation exposure while maintaining measurement precision.
2Measurement precision
If sufficient radiation is used to obtain accurate spectral data, then measurement precision improves, but the required irradiation increases by a factor of 10
Solution Approach 1:
The patent performs preliminary spatial smoothing of the attenuation coefficients before material decomposition. This pre-processing creates a regularized structural framework that reduces statistical noise in the spectral data, allowing accurate material characterization with lower photon counts. The smoothing operation is performed in advance to establish a stable geometric basis that reduces the radiation dose required for subsequent measurements.
Solution Approach 2:
The patent implements an iterative optimization process where the decomposition result feeds back into the reconstruction process. The algorithm iteratively refines the equivalent thickness estimates by comparing predicted spectra with measured spectra and adjusting the decomposition parameters accordingly. This feedback mechanism allows the system to achieve high measurement precision with fewer photons by continuously optimizing the solution based on the actual spectral data obtained at lower irradiation levels.
3Device complexity
If conventional decomposition methods are used without spatial smoothing, then processing is simpler, but image quality and characterization accuracy deteriorate
Solution Approach 1:
The patent applies preliminary spatial smoothing to the attenuation map before decomposition. This pre-processing step creates a regularized structural framework that guides the subsequent material decomposition, improving image quality and characterization accuracy. The smoothing operation is performed in advance to establish a stable geometric basis that reduces noise and enhances the reliability of the decomposition results.
Solution Approach 2:
The patent changes the parameter representation by introducing a smoothed attenuation map as an intermediate parameter. Instead of directly decomposing the raw spectral data, the method transforms the problem into the spatial domain by first creating a smoothed structural representation. This parameter transformation allows the decomposition to operate on a regularized basis, improving image quality while the smoothing parameter can be adjusted to balance complexity and accuracy.
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 allows for accurate characterization of objects with lower exposure to radiation, improving image quality and reducing the required irradiation by a factor of 10, while maintaining equivalent image quality to prior methods.
Implementation Method 1
irradiating the object with the radiation source and detecting radiation transmitted by the object using the radiation detector
Data Source
AI summary
The invention is a method for characterizing an object (20), comprising the following steps:a) placing the object between a radiation source (10) and a radiation detector (30);b) irradiating the object with the radiation source and detecting radiation transmitted by the object (14) using the radiation detector, the radiation detector defining a plurality of pixels;c) for each pixel (30i), forming an energy spectrum (Si) of the detected radiation, each spectrum comprising at least two distinct energy bands;d) from each spectrum formed in c), estimating, in each pixel, at least two equivalent thicknesses ({circumflex over (L)}i,1 . . . {circumflex over (L)}i,M,{circumflex over (L)}′i,1 . . . {circumflex over (L)}′i,M) respectively associated with at least two basic materials (mat1 . . . matM,mat′1 . . . mat′M);wherein the method comprises, following d), the following steps:e) from the equivalent thicknesses resulting from d), calculating a structural parameter (Pi) of the object in various pixels (30i);f) spatially smoothing the structural parameter calculated in a plurality of pixels;g) from the structural parameter smoothed in each pixel, and from each spectrum formed in c), estimating, in each pixel, regularized equivalent thicknesses ({circumflex over (L)}i,m=1|Pi* . . . {circumflex over (L)}i,m=M|Pi*,{circumflex over (L)}′i,m=1|Pi* . . . {circumflex over (L)}i,m=M|Pi*).