# US 9,430,827 B2 · Segmentation of a calcified blood vessel > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 9,430,827 B2 - Document ID: US9430827B2 - Status: Granted - Kind: B2 - Application number: 14/148,758 - Filed: 2014-01-07 - Published: 2014-12-04 - Granted: 2016-08-30 - Earliest claimed: 2013-05-31 - Assignees: Siemens Aktiengesellschaft - Applicants: Siemens Aktengesellschaft - Inventors: Michael Kelm; Felix Lugauer; Jingdan Zhang; Yefeng Zheng - Web page: https://patentgrep.com/patent/US9430827B2 ## CPC - G06T 7/0012: {Biomedical image inspection} - G06T 7/12: Edge-based segmentation - G06T 7/143: involving probabilistic approaches, e.g. Markov random field [MRF] modelling - G06T 7/149: involving deformable models, e.g. active contour models - G06T 7/162: involving graph-based methods - G06T 2207/10081: Computed x-ray tomography [CT] - G06T 2207/20076: Probabilistic image processing - G06T 2207/30048: Heart; Cardiac - G06T 2207/30101: Blood vessel; Artery; Vein; Vascular - G06T 2207/30172: Centreline of tubular or elongated structure - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ## Abstract A method is disclosed for segmentation of a calcified blood vessel in image data. An embodiment of the method includes providing a vesseltree representation of the blood vessel; providing a number of preliminary boundary representations of a number of cross-sections of the blood vessel; providing a number of intensity profiles in the image data in the number of cross-sections; determining a calcification in the cross-section based on the intensity profile; and correcting each preliminary boundary representation into a corrected boundary representation which excludes the calcification from an inner part of the blood vessel. A segmentation system is also disclosed. ## Claims ### Claim 1 A method for segmentation of a calcified blood vessel in image data, comprising: providing a vesseltree representation of the blood vessel; providing a number of preliminary boundary representations of a number of cross-sections of the blood vessel; providing a number of intensity profiles in the image data in the number of cross-sections; obtaining a threshold intensity level based on ranges of an intensity distribution of the intensity profile corresponding to at least one cross-section of the number of cross-sections; determining a calcification in the at least one cross-section based on the threshold intensity level; and correcting each preliminary boundary representation into a corrected boundary representation which excludes the calcification from an inner part of the blood vessel. ### Claim 2 (depends on 1) The method of claim 1, wherein the providing the number of intensity profiles determines the number of intensity profiles in the number of cross-sections along a number of profile rays from one seed point within the blood vessel in each cross-section towards the preliminary boundary representation. ### Claim 3 (depends on 1) The method of claim 1, wherein the determining the calcification determines the calcification in a region having an intensity above the threshold level. ### Claim 4 (depends on 3) The method of claim 3, wherein the image data are based on X-ray acquisition and wherein the threshold intensity level is above 576 HU. ### Claim 5 (depends on 1) The method of claim 1, wherein a result from the determination of the calcification is compared to an extension of the preliminary boundary representation for validation of the result. ### Claim 6 (depends on 1) The method of claim 1, wherein the vesseltree representation comprises a centerline of the blood vessel. ### Claim 7 (depends on 6) The method of claim 6, wherein the providing the vesseltree includes recentering the centerline at least once. ### Claim 8 (depends on 1) The method of claim 1, further comprising: warping the image data such that the vesseltree representation is aligned along a straight line and at least one of the number of preliminary and corrected boundary representations are aligned parallel to one another. ### Claim 9 (depends on 1) The method of claim 1, wherein the providing the number of preliminary boundary representations includes deriving likelihood values of candidate points in the respective cross-section. ### Claim 10 (depends on 9) The method of claim 9, wherein the deriving derives the likelihood values using a trained classifier algorithm. ### Claim 11 A method for segmentation of a calcified blood vessel in image data, comprising: providing a vesseltree representation of the blood vessel; providing a number of preliminary boundary representations of a number of cross-sections of the blood vessel; providing a number of intensity profiles in the image data in the number of cross-sections; determining a calcification in at least one of the cross-sections based on the corresponding intensity profile; correcting each preliminary boundary representation into a corrected boundary representation which excludes the calcification from an inner part of the blood vessel; providing an image representation of the calcified blood vessel; providing a start surface model, including a mesh with a plurality of vertices connected by edges; defining, for each vertex, a ray normal to the surface model at the position of the vertex; assigning more than two labels to each vertex, each label representing a candidate position of the vertex on the ray; providing, based in the corrected boundary representation, a representation of likelihoods for each candidate position the likelihood referring to whether the candidate position corresponds to a surface point of the blood vessel in the image representation; defining a first order Markov Random Field with discrete multivariate random variables, the random variables comprising the labels of the candidate positions and the representation of likelihoods; and finding an optimal segmentation of the calcified blood vessel by using a maximum a posteriori estimation in this Markov Random Field. ### Claim 12 A segmentation system for segmentation of a calcified blood vessel in image data, comprising: an input interface for the image data; a first provision unit configured to provide a vesseltree representation of the blood vessel, a second provision unit configured to provide a number of preliminary boundary representations of a number of cross-sections of the blood vessel; a third provision unit configured to provide a number of intensity profiles in the image data in the number of cross-sections; a determination unit configured to, obtain the threshold intensity level based on ranges of an intensity distribution of the intensity profile corresponding to at least one cross-section of the number of cross-sections, and determine a calcification in the at least one cross-section based on the threshold intensity level; and a correction unit configured to correct each preliminary boundary representation into a corrected boundary representation which excludes the calcification from an inner part of the blood vessel. ### Claim 13 (depends on 12) A tomographic imaging device comprising: an acquisition unit; and the segmentation system of claim 12. ### Claim 14 (depends on 1) A non-transitory computer program product directly loadable into a processor of a programmable segmentation system comprising program code segments to perform the method of claim 1 when the computer program product is executed on the segmentation system. ### Claim 15 (depends on 7) The method of claim 7, wherein the providing the vesseltree includes recentering the centerline at least once after correcting the preliminary boundary representation. ### Claim 16 (depends on 1) A non-transitory computer readable medium including program code segments for, when executed on a programmable segmentation system, causing the programmable segmentation system to implement the method of claim 1. ### Claim 17 (depends on 11) A non-transitory computer readable medium including program code segments for, when executed on a programmable segmentation system, causing the programmable segmentation system to implement the method of claim 11. ### Claim 18 (depends on 1) The method of claim 1, wherein the threshold level is based on a variance of the intensity profile corresponding to the at least one cross-section. ### Claim 19 (depends on 1) The method of claim 1, wherein the obtaining obtains the threshold intensity level based on a variance of the intensity profile corresponding to the at least one cross-section. ### Claim 20 (depends on 1) The method of claim 1, wherein the correcting corrects each preliminary boundary representation into the corrected boundary representation using a piecewise function.