# US 10,311,606 B2 · Correction of beam hardening artifacts in microtomography for samples imaged in containers > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,311,606 B2 - Document ID: US10311606B2 - Status: Granted - Kind: B2 - Application number: 15/504,311 - Filed: 2015-08-15 - Published: 2017-08-10 - Granted: 2019-06-04 - Earliest claimed: 2014-08-16 - Applicants: FEI Company - Inventors: Jeremy James Holt; Andrew Maurice Kingston; Adrian Paul Sheppard - Web page: https://patentgrep.com/patent/US10311606B2 ## CPC - G06T 12/20: Inverse problem, i.e. transformations from projection space into object space - G06F 18/23: Clustering techniques - G06F 18/2415: based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate - G06T 7/11: Region-based segmentation - G06T 12/30: Image post-processing, e.g. metal artefact correction - G06T 2207/10081: Computed x-ray tomography [CT] - G06T 2207/10116: X-ray image - G06T 2207/30181: Earth observation - G06T 2211/408: Dual energy - G06T 2211/424: Iterative - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract Provided are improved referenceless multi-material beam hardening correction methods, with an emphasis on maintaining data quality for real-world imaging of geologic materials with a view towards automation. A referenceless post reconstruction (RPC) correction technique is provided that applies the corrections in integrated attenuation space. A container-only pre-correction technique also is provided to allow automation of the segmentation process required for beam hardening correction methods. ## Claims ### Claim 1 A method of correcting tomographic reconstruction for beam hardening, the method comprising: (a) reconstructing an initial tomogram from tomographic projection data; (b) segmenting the tomogram into two or more phases; (c) based on the segmented tomogram, calculating a referenceless post reconstruction correction (RPC) correction in integrated attenuation space; (d) applying the RPC correction to tomographic projection data to correct for beam hardening effects; and (e) reconstructing a final tomogram from the corrected tomographic projection data. ### Claim 2 (depends on 1) The method of claim 1 in which applying RPC further comprises reprojecting each phase in the segmented tomogram to create a simulated monochromatic projection for each material, the simulated monochromatic projections calculated in the space of integrated attenuation. ### Claim 3 (depends on 1) The method of claim 1, further comprising applying a container-only pre-correction to the tomogram to correct for beam hardening effects due to a container holding the sample material but not to the sample itself. ### Claim 4 (depends on 3) The method of claim 3, further comprising generating the container only pre-correction by selecting a set of rays that pass only through the container, and calculating an integrated attenuation for the container based on the selected set of rays. ### Claim 5 (depends on 3) The method of claim 3 further comprising receiving pre-defined container shape data and generating the container only pre-correction based on the pre-defined container shape data. ### Claim 6 (depends on 3) The method of claim 3 in which segmenting the tomogram provides container shape data which is used to generate the container only pre-correction. ### Claim 7 (depends on 1) The method of claim 1 in which the segmenting includes performing a k-means clustering technique in which the radial distance and grayscale intensity are used to distinguish the phases. ### Claim 8 (depends on 1) The method of claim 1 in which the segmenting comprises part of an iterative segmentation and reconstruction process for the initial reconstruction, including the steps: (a) determining one or more estimated material characteristics for multiple volume elements in the sample using a tomographic reconstruction algorithm; (b) modifying the one or more estimated material characteristic by reference to stored material characteristic data based on a probabilistic classification to determine the most likely material in the materials dictionary for each volume element; (c) performing one or more additional iterations of the tomographic reconstruction algorithm where each iteration updates the one or more estimated material characteristic for the volume elements; and (d) labeling the reconstructed volume representing the sample into regions of materials having similar characteristics. ### Claim 9 (depends on 1) The method of claim 1 in which reconstructing the final tomogram further comprises: (a) determining one or more estimated material characteristics for multiple volume elements in the sample using a tomographic reconstruction algorithm; (b) modifying the one or more estimated material characteristic by reference to stored material characteristic data based on a probabilistic classification to determine the most likely material in the materials dictionary for each volume element; (c) performing one or more additional iterations of the tomographic reconstruction algorithm where each iteration updates the one or more estimated material characteristic for the volume elements; and (d) labeling the reconstructed volume representing the sample into regions of materials having similar characteristics. ### Claim 10 (depends on 1) The method of claim 1, wherein in the calculating a referenceless post reconstruction correction (RPC) correction in integrated attenuation space, N-vectors are determined for each pixel. ### Claim 11 A method of correcting tomographic reconstruction for beam hardening, the method comprising: (a) reconstructing an initial tomogram from tomographic projection data; (b) applying a container-only pre-correction to the tomogram to correct for beam hardening effects due to a container holding the sample material but not to the sample material itself; (c) segmenting the tomogram into two or more phases; (d) based on the segmented tomogram, calculating a referenceless post reconstruction correction (RPC) correction; (e) applying the RPC correction to tomographic projection data to correct for beam hardening effects; and (f) reconstructing a final tomogram from the corrected tomographic projection data. ### Claim 12 (depends on 11) The method of claim 11 in which applying RPC further comprises reprojecting each phase in the segmented tomogram to create a simulated monochromatic projection for each material, the simulated monochromatic projections calculated in the space of integrated attenuation. ### Claim 13 (depends on 11) The method of claim 11, further comprising generating the container only pre-correction by selecting a set of rays that pass only through the container, and calculating an integrated attenuation for the container based on the selected set of rays. ### Claim 14 (depends on 11) The method of claim 11, further comprising receiving pre-defined container shape data and generating the container only pre-correction based on the pre-defined container shape data. ### Claim 15 (depends on 11) The method of claim 11 in which segmenting the tomogram provides container shape data which is used to generate the container only pre-correction. ### Claim 16 (depends on 11) The method of claim 11 in which the segmenting includes performing a k-means clustering technique in which the radial distance and grayscale intensity are used to distinguish the phases. ### Claim 17 (depends on 11) The method of claim 11 in which reconstructing the final tomogram further comprises: (a)determining one or more estimated material characteristics for multiple volume elements in the sample using a tomographic reconstruction algorithm; (b)modifying the one or more estimated material characteristic by reference to stored material characteristic data based on a probabilistic classification to determine the most likely material in the materials dictionary for each volume element; (c) performing one or more additional iterations of the tomographic reconstruction algorithm where each iteration updates the one or more estimated material characteristic for the volume elements; and (d) labeling the reconstructed volume representing the sample into regions of materials having similar characteristics. ### Claim 18 (depends on 11) The method of claim 11 in which segmenting the tomogram into two or more phases further comprises separating into at least one phase of an agglomerate material. ### Claim 19 (depends on 18) The method of claim 18, further comprising referencing an agglomerate material library to identify the agglomerate material. ### Claim 20 (depends on 1, 2, 3, 4, 5, 6, 7, 8) 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 any of claims 1-8.