# US 12,223,569 B2 · Computer-implemented method for handling artifacts in multi-energy computed tomography, x-ray imaging device, computer program and electronically readable storage medium > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,223,569 B2 - Document ID: US12223569B2 - Status: Granted - Kind: B2 - Application number: 17/529,459 - Filed: 2021-11-18 - Published: 2022-05-26 - Granted: 2025-02-11 - Earliest claimed: 2020-11-20 - Assignees: Siemens Healthineers AG - Applicants: Siemens Healthcare GmbH - Inventors: Bernhard Schmidt; Katharine Grant; Thomas Flohr - Web page: https://patentgrep.com/patent/US12223569B2 ## CPC - G06T 11/008 - A61B 6/032: {Transmission computed tomography [CT]} - A61B 6/5258: {involving detection or reduction of artifacts or noise} - G06T 7/0012: {Biomedical image inspection} - G06V 10/22: by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition - G06T 2207/10081: Computed x-ray tomography [CT] - G06T 2207/10116: X-ray image - G06T 2207/30061: Lung - G06V 2201/03: Recognition of patterns in medical or anatomical images - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING ## Abstract A computer-implemented method of an embodiment is for automatically estimating and/or correcting an error due to artifacts in a multi-energy computed tomography result dataset relating to at least one target material. In an embodiment, the method includes determining at least one first subregion of the imaging region, which is free from the target material and contains at least one, in particular exactly one, second material with known material-specific energy dependence of x-ray attenuation; for each first subregion, comparing the image values of the energy dataset for each voxel, taking into account the known energy dependence, to determine deviation values indicative of artifacts; and for at least a part of the at least one remaining second subregion of the imaging region, calculating estimated deviation values by interpolating and/or extrapolating from the determined deviation values in the first subregion, the estimated deviation values being used as estimated error due to artifacts. ## Claims ### Claim 1 A computer-implemented method for at least one of automatically estimating or automatically correcting an error due to artifacts in a multi-energy computed tomography result dataset relating to at least one target material, at least two three-dimensional energy datasets of an imaging region of a patient being acquired using an x-ray imaging device using different x-ray energy spectra, and a result dataset being determined by evaluating the at least two three-dimensional energy datasets using material-specific energy dependences of x-ray attenuation, the computer-implemented method comprising: determining at least one first subregion, of the imaging region, free from the at least one target material and containing at least one second material with known material-specific energy dependence of x-ray attenuation; comparing, for each respective first subregion of the at least one first subregion, image values of each of the at least two three-dimensional energy datasets for each voxel, taking into account known energy dependence, to determine deviation values indicative of artifacts; and calculating, for at least a part of at least one remaining second subregion of the imaging region, estimated deviation values by at least one of interpolating or extrapolating from the deviation values indicative of artifacts in a respective first subregion, wherein the estimated deviation values are used as estimated error due to artifacts. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein at least one of at least one energy value is corrected according to the estimated deviation values before determining result values of the result dataset; additional to the result dataset, an error dataset showing at last one of spatially resolved estimated deviation values and an error propagated through the evaluating the at least two three-dimensional energy datasets using material-specific energy dependences of x-ray attenuation is determined; or the result dataset is modified according to the estimated deviation values. ### Claim 3 (depends on 1) The computer-implemented method of claim 1, wherein the at least one first subregion is determined by segmenting the at least two three-dimensional energy datasets regarding at least the at least one second material. ### Claim 4 (depends on 1) The computer-implemented method of claim 1, wherein at least one subregion containing a second material having an at least essentially energy-spectra invariant behavior is used as the at least one first subregion. ### Claim 5 (depends on 1) The computer-implemented method of claim 1, wherein at least one of air or fat tissue is used as the second material. ### Claim 6 (depends on 5) The computer-implemented method of claim 5, wherein the at least one first subregion, in a case of air as the second material, includes a region outside at least one of the patient or at least one hollow organ comprising air. ### Claim 7 (depends on 1) The computer-implemented method of claim 1, wherein, for the at least one of interpolating or extrapolating, at least one of nearest-neighbor interpolation, inverse distance weighting or spline interpolation is employed. ### Claim 8 (depends on 1) The computer-implemented method of claim 1, wherein the at least two three-dimensional energy datasets are acquired by spiral computed tomography, and wherein the artifacts comprise spiral artifacts. ### Claim 9 (depends on 1) The computer-implemented method of claim 1, wherein the at least one of interpolating or extrapolating is performed taking into account at least one expected property of at least one of the artifacts. ### Claim 10 (depends on 1) The computer-implemented method of claim 1, wherein at least one of iodine is used as the target material; or at least one material map is determined as the result dataset. ### Claim 11 An X-ray imaging device, comprising: at least one acquisition arrangement including an x-ray source and an x-ray detector; and a controller to perform determining at least one first subregion, of an imaging region, free from at least one target material and containing at least one second material with known material-specific energy dependence of x-ray attenuation; comparing, for each respective first subregion of the at least one first subregion, image values of each of at least two three-dimensional energy datasets for each voxel, taking into account known energy dependence, to determine deviation values indicative of artifacts; and calculating, for at least a part of at least one remaining second subregion of the imaging region, estimated deviation values by at least one of interpolating or extrapolating from the deviation values indicative of artifacts in a respective first subregion, wherein the estimated deviation values are used as estimated error due to artifacts. ### Claim 12 (depends on 1) A non-transitory computer program product storing a computer program which, when the computer program is executed on a control device of an x-ray imaging device, performs the method of claim 1. ### Claim 13 (depends on 1) A non-transitory electronically readable storage medium, storing a computer program which, when the computer program is executed on a control device of an x-ray imaging device, performs the method of claim 1. ### Claim 14 (depends on 2) The computer-implemented method of claim 2, wherein the at least one first subregion is determined by segmenting the energy datasets regarding at least the at least one second material. ### Claim 15 (depends on 3) The computer-implemented method of claim 3, wherein at least one of threshold segmenting or an anatomical atlas is used. ### Claim 16 (depends on 4) The computer-implemented method of claim 4, wherein an expected change in an image value between an energy spectra for the second material is relatively lower than a threshold value. ### Claim 17 (depends on 16) The computer-implemented method of claim 16, wherein the expected change in the image value between energy spectra for the second material is relatively less than one fifth of a threshold expected artifact-induced change. ### Claim 18 (depends on 2) The computer-implemented method of claim 2, wherein, for the at least one of interpolating or extrapolating, at least one of nearest-neighbor interpolation, inverse distance weighting or spline interpolation is employed. ### Claim 19 (depends on 2) The computer-implemented method of claim 2, wherein the energy datasets are acquired by spiral computed tomography, and wherein the artifacts comprise spiral artifacts. ### Claim 20 (depends on 9) The computer-implemented method of claim 9, wherein the at least one expected property of at least one of the artifacts is an expected spatial frequency or an expected spatial frequency range of the artifact. ### Claim 21 (depends on 11) The X-ray imaging device of claim 11, wherein the X-ray imaging device is a computed tomography device.