Tomographic reconstruction for material characterization

Patent metadata

Field	Value
Publication number	US-10354418-B2
Application number	US-201515504302-A
Country	US
Kind code	B2
Filing date	Aug 15, 2015
Priority date	Aug 16, 2014
Publication date	Jul 16, 2019
Grant date	Jul 16, 2019

Abstract

Some embodiments of the invention provide a method of determining a material characteristic of material in a sample by iterative tomographic reconstruction. The method conducts one or more X-ray tomography scans of a sample, and then determines one or more estimated material characteristics, such as atomic number and density, for multiple volume elements in the sample using a tomographic reconstruction algorithm. These estimated material characteristics are then modified by reference to stored known material characteristic data. Preferably, determining the composition of the sample volume during reconstruction includes segmenting the sample into regions of common composition, the segmenting being performed during iterative reconstruction instead of being based on the voxel characteristics determined upon the completion of iterative reconstruction. Preferred versions will perform one or more additional iterations of the tomographic reconstruction algorithm, where each iteration updates the one or more estimated material characteristics for the volume elements.

First claim

The invention claimed is:

1. A method of determining the atomic number and density of material in a sample by iterative tomographic reconstruction, comprising:
(a) directing x-rays toward a sample from multiple directions;
(b) measuring the x-ray intensity of x-rays that have traversed the sample;
(c) calculating an estimated atomic number and calculating an estimated density for multiple volume elements in the sample using a tomographic reconstruction algorithm;
(d) modifying the estimated atomic numbers and estimated densities by reference to atomic numbers and densities of known materials from a materials library; and
(e) performing one or more additional iterations of the tomographic reconstruction algorithm where each iteration updates the modified atomic numbers and densities for the volume elements.

2. The method of claim 1 in which modifying the estimated atomic numbers and estimated atomic densities includes calculating update values for the estimated atomic numbers and estimated atomic densities.

3. The method of claim 2 in which at least one of the additional iterations further comprises modifying the updated estimated atomic numbers and estimated densities using atomic numbers and densities of known materials from the materials library.

4. The method of claim 1 in which modifying the estimated atomic numbers and estimated densities by reference to atomic numbers and densities of known materials from a materials library includes modifying based on a probabilistic classification to determine a most likely material in the materials library for each volume element.

5. The method of claim 4 , in which modifying the estimated atomic numbers and estimated densities for at least one of the iterations includes modifying the numbers with a constrained update making the modified numbers to be consistent with known material properties in the materials library.

6. The method of claim 1 further comprising segmenting the iterative tomographic reconstruction of the sample into regions of materials having similar atomic numbers and densities.

7. The method of claim 6 in which the segmenting occurs at least once during the iterative tomographic reconstruction of the sample.

8. The method of claim 1 in which directing x-rays toward a sample from multiple directions includes two or more steps, each step comprising directing x-rays toward the sample with an energy or energy spectrum different from that used in at least one other step.

9. The method of claim 1 in which the x-rays directed towards the sample contain a spectrum of energies and measuring the x-ray intensity of x-rays that have traversed the sample further comprises measuring information about the energy spectrum of x-rays that have traversed the sample.

10. The method of claim 1 in which the materials library includes minerals.

11. The method of claim 10 in which the materials library is limited to materials expected to be found in the sample.

12. The method of claim 1 in which the tomographic reconstruction algorithm comprises Algebraic Reconstruction Technique (ART), Simultaneous ART, Simultaneous iterative reconstruction technique (SIRT), Ordered subset SIRT, Multiplicative algebraic reconstruction technique, Maximum likelihood expectation-maximization, Ordered subset expectation-maximization, Ordered subset convex algorithm, Iterative coordinate descent (ICD), Ordered subset ICD, or Model-based iterative reconstruction.

13. The method of claim 1 in which determining an estimated atomic number and an estimated density for multiple volume elements in the sample using a tomographic reconstruction algorithm includes correcting using a tomographic reconstruction algorithm that corrects or accounts for beam hardening.

14. The method of claim 1 in which directing x-rays toward a sample from multiple directions includes directing x-rays from a synchrotron.

15. The method of claim 1 in which directing x-rays toward a sample from multiple directions includes directing x-rays generated by the impact of an electron beam with a target.

16. The method of claim 1 in which modifying the estimated atomic numbers and estimated densities by reference to atomic numbers and densities of known materials from a materials library includes modifying the estimated atomic numbers and estimated densities by reference to mass attenuation tables.

17. A tomography system, comprising:
an X-ray beam source to be directed through a sample;
a rotating sample holder;
an X-ray detector for detecting energy from the X-ray beam source; and
a system controller operatively connected to the X-ray beam source, the rotating sample holder, and the X-ray detector, and including a program memory including computer instructions for performing the method of claim 1 .

Assignees

• Fei Co

Inventors

• Recur Benoit Mathieu Baptiste
• Paziresh Mahsa
• Myers Glenn Robert
• Kingston Andrew Maurice
• Latham Shane Jamie

Classifications

• G06T12/30

  Image post-processing, e.g. metal artefact correction · CPC title

• G06T12/20 Primary

  Inverse problem, i.e. transformations from projection space into object space · CPC title

• G06F18/23

  Clustering techniques · CPC title

• G06F18/2415

  based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate · CPC title

• G06T2207/10116

  X-ray image · CPC title