Effective Atomic Number Estimation via Transmission Spectrum Likelihood
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for measuring the effective atomic number of materials using X or gamma spectroscopy lack precision and reliability, leading to inaccurate characterization in medical imaging and non-destructive testing.
Innovation Solution
A method involving the measurement of a transmission spectrum across multiple energy channels, calculation of a likelihood function for effective atomic number and thickness, and interpolation of calibration spectra to estimate the effective atomic number using a probabilistic approach, maximizing the likelihood function to achieve accurate results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional direct conversion spectrometric sensors are used to measure effective atomic number, then the measurement process is simple, but the precision and reliability of the measurement are insufficient
Solution Approach 1:
The invention changes the measurement parameters by using transmission spectra at multiple energy levels (at least two different energy levels) instead of single-energy measurements. This allows the system to capture the energy-dependent attenuation characteristics of materials, enabling more precise determination of effective atomic number through the relationship between attenuation coefficients and atomic number at different energies.
Solution Approach 2:
The invention introduces an intermediary computational process that uses the measured transmission spectra at multiple energy levels to calculate the effective atomic number. The system uses the ratio of attenuation coefficients at different energy levels as an intermediary parameter to determine the effective atomic number, which resolves the contradiction by adding computational complexity while achieving higher measurement precision.
2Reliability
If single-energy X or gamma spectroscopy is used, then the measurement is quick and simple, but the reliability of material characterization is insufficient
Solution Approach 1:
The invention performs preliminary measurements by acquiring transmission spectra at multiple energy levels before final analysis. This preliminary action of collecting multi-energy data ensures reliable material characterization, and the subsequent processing uses this pre-collected information to determine effective atomic number accurately, accepting the time investment for improved reliability.
Solution Approach 2:
The invention uses excessive action by measuring at more energy levels than the minimum required (using at least two different energy levels). This partial or excessive measurement approach ensures that sufficient data is collected to reliably characterize materials, particularly for distinguishing between different material compositions that may have similar single-energy attenuation characteristics.
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 method provides a reliable and precise estimation of the effective atomic number, enhancing the accuracy of material characterization in medical imaging and non-destructive testing applications.
Implementation Method 1
an incident photon on this element creates a cloud of electronic charges there (typically 10,000 electrons for a 60 keV X photon)
Implementation Method 2
the photoelectric effect (p = 4.62)
Implementation Method 3
a transmission spectrum is measured of a sample of said material in a plurality (N) energy channels of said spectral band
Data Source
Figure 1
Figure 2
Figure 3A~3C
AI summary
The invention relates to a method for estimating the effective atomic number of a material from a transmission spectrum of said material. First (230), a likelihood function of the effective atomic number and the thickness of the material is calculated on the basis of the transmission spectrum as well as calibration spectra obtained in a previous calibration phase for a plurality of samples of calibration materials of known effective atomic numbers and known thicknesses. Then (240), the effective atomic number (I) of the material is estimated on the basis of values of the likelihood function.