WO2022000734A1 - Procédé et système d'extraction de point sur une ligne centrale d'aorte sur la base d'une image de séquence de tomodensitométrie - Google Patents

Procédé et système d'extraction de point sur une ligne centrale d'aorte sur la base d'une image de séquence de tomodensitométrie Download PDF

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WO2022000734A1
WO2022000734A1 PCT/CN2020/110231 CN2020110231W WO2022000734A1 WO 2022000734 A1 WO2022000734 A1 WO 2022000734A1 CN 2020110231 W CN2020110231 W CN 2020110231W WO 2022000734 A1 WO2022000734 A1 WO 2022000734A1
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center
circle
threshold
point
radius
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PCT/CN2020/110231
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English (en)
Chinese (zh)
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冯亮
王之元
刘广志
陈韵岱
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苏州润迈德医疗科技有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/40—Image enhancement or restoration using histogram techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/136—Segmentation; Edge detection involving thresholding
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/187—Segmentation; Edge detection involving region growing; involving region merging; involving connected component labelling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G06T7/66—Analysis of geometric attributes of image moments or centre of gravity
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2200/00—Indexing scheme for image data processing or generation, in general
    • G06T2200/04—Indexing scheme for image data processing or generation, in general involving 3D image data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10081—Computed x-ray tomography [CT]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30008—Bone
    • G06T2207/30012—Spine; Backbone
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30048—Heart; Cardiac

Definitions

  • the present invention relates to the technical field of coronary medicine, in particular to a method and system for picking up points on the central line of the aorta based on CT sequence images.
  • Cardiovascular disease is the leading cause of death in the industrialized world.
  • the major form of cardiovascular disease is caused by the chronic accumulation of fatty substances in the inner tissue layers of the arteries supplying the heart, brain, kidneys and lower extremities.
  • Progressive coronary artery disease restricts blood flow to the heart. Due to the lack of accurate information provided by current non-invasive tests, many patients require invasive catheter procedures to evaluate coronary blood flow. Therefore, there is a need for a non-invasive method for quantifying blood flow in human coronary arteries to assess the functional significance of possible coronary artery disease. A reliable assessment of arterial volume will therefore be important for treatment planning addressing the patient's needs.
  • hemodynamic properties such as fractional flow reserve (FFR) are important indicators for determining optimal treatment for patients with arterial disease. Routine assessment of fractional flow reserve uses invasive catheterization to directly measure blood flow properties, such as pressure and flow rate. However, these invasive measurement techniques present risks to patients and can result in significant costs to the health care system.
  • FFR fractional flow reserve
  • Computed tomography arterial angiography is a computed tomography technique used to visualize arterial blood vessels.
  • a beam of X-rays is passed from a radiation source through a region of interest in the patient's body to obtain projection images.
  • the present invention provides a method and system for picking up points on the center line of the aorta based on CT sequence images, so as to solve the problem that the CT data in the prior art cannot obtain the center of gravity of the heart and the spine, or the method for obtaining the center of gravity of the heart and the spine is complicated The problem.
  • the present application provides a method for picking up points on the centerline of the aorta based on CT sequence images, including:
  • the above-mentioned method for picking up points on the centerline of the aorta based on CT sequence images starts layered slices from the top layer of the CT image, and the method for obtaining a two-dimensional image group includes:
  • Slicing is started from the top layer of the new image, resulting in a two-dimensional image group.
  • the two-dimensional image group is subjected to binarization processing, and the method for obtaining the binarized image group includes:
  • m is a positive integer
  • Q m represents the grayscale value corresponding to the mth pixel point PO
  • P(m) represents the pixel value corresponding to the mth pixel point PO.
  • the sequence of Method CT image pickup point based on the center line of the aorta, the threshold N ⁇ N obtained from each of the slice image group of the two values of 1, R R threshold 1 ⁇ m, where N represents the number of pixel points, then detect a circle in the slice of the kth layer, take the center of the circle as the center P 5k , and the radius of the circle corresponding to the center P 5k is R
  • the methods of k include:
  • the above-mentioned method for picking up points on the centerline of the aorta based on CT sequence images the method for establishing a search engine list for each layer of the slices in the binarized image group includes:
  • the search engine list includes: a point list and a radius list, and the points with a pixel value of 1 extracted from the binarized image of each layer are correspondingly filled into the point list.
  • step D Set the threshold of the number of pixels in the point list of each layer of the slice to be N threshold 1 , and the radius threshold to be R threshold 1 , and perform step E for each layer of the slice in turn from the top layer to the process of step 1;
  • N k ⁇ N threshold 1 , R k ⁇ R threshold 1 ⁇ m If N k ⁇ N threshold 1 , R k ⁇ R threshold 1 ⁇ m, then detect 3 circles in the slice of the kth layer, if 3 circles are detected, go to step I, if 3 circles are not detected The circle then carries out the described step H;
  • N k > N threshold 1 then re-determine the center of the circle, take the point with the closest distance between the center of the circle in the k-1 slice and the end point D in the point list as the center O k , and proceed to step I, If no circle is detected, go to step H;
  • the above-mentioned method for picking up points on the centerline of the aorta based on CT sequence images further includes: filtering the center P 5k to generate a new point list, including:
  • step E If the gray value of the center P 5k on the new image from which the lungs, descending aorta, spine, and ribs are removed is less than 0, repeat the process from step E to step I until the radius is found R 1 ⁇ R threshold 2 , and the center P 5k of the circle whose gray value is greater than or equal to 0;
  • the above-mentioned method for picking up points on the centerline of the aorta based on CT sequence images further includes: filtering the radius R k to generate a new radius list, including:
  • N threshold 2 Set another number threshold N threshold 2 of the pixel points in the point list of each layer of the slice, if N k ⁇ N threshold 2 , compare the circle center P 5k with the end point in the point list distance L, if L>L threshold , repeat steps E to N until the number of points in the point list N k ⁇ N threshold 2 , or L ⁇ L threshold ;
  • N N k ⁇ N threshold 2 , or N k ⁇ N threshold 2 , L ⁇ L threshold , replace the radius value of the point far away from the center P 5k with the average radius value of the remaining points, as R k , set The radius R k is filled into the radius list, a new radius list is generated, and points on the centerline of the aorta that meet the conditions are obtained.
  • the present application provides a system for picking up points on the centerline of the aorta based on CT sequence images, which is used in the above-mentioned method for picking up points on the centerline of the aorta based on CT sequence images, including: sequentially connecting images Reader, slice device, binarization device and center point pick-up device;
  • the image reader for reading CT images
  • the slicing device is used for layered slicing from the top layer of the CT image to obtain a two-dimensional image group;
  • the binarization device configured to perform binarization processing on the two-dimensional image group to obtain a binarized image group
  • the center point picking device includes: a search unit, a comparison unit, and a center point picking unit connected in sequence;
  • the search unit connected to the binarization device, is used to establish a search engine list for each layer of the slices in the binarized image group, and to search for the circle of each layer of slices;
  • the comparison unit is used to compare the number of pixels and the radius of the circle in the search engine list of each layer;
  • the center point picking unit is used to find the center point that meets the conditions from the slices of each layer, and if the center point that meets the conditions cannot be found, searches for the center point of the next layer of slices.
  • the present application provides a computer storage medium, and when the computer program is executed by a processor, the above-mentioned method for picking up a point on an aortic centerline based on a CT sequence image is implemented.
  • the present application provides a method for picking up points on the centerline of the aorta based on CT sequence images, which is a new method for acquiring points on the centerline of the aorta, which has the advantages of fast and accurate extraction and fast calculation speed.
  • FIG. 1 is a flowchart of a method for picking up a point on the centerline of the aorta based on a CT sequence image of the present application
  • Fig. 2 is the flow chart of S1000 of this application.
  • Fig. 3 is the flow chart of S3000 of this application.
  • FIG. 4 is a structural block diagram of the system for picking up points on the centerline of the aorta based on CT sequence images of the present application;
  • CT data in the prior art is not screened, resulting in a large amount of computation, slow computation speed and inaccurate computation.
  • the present application provides a method for picking up points on the centerline of the aorta based on CT sequence images, as shown in FIG. 1 , including:
  • S1100 removing new images of the lungs, descending aorta, spine, and ribs from the CT image, including: setting grayscale thresholds of pixels of the lungs, descending aorta, spine, and ribs, respectively, from the CT image remove the corresponding image;
  • m is a positive integer
  • Q m represents the grayscale value corresponding to the mth pixel point PO
  • P(m) represents the pixel value corresponding to the mth pixel point PO.
  • the search engine list includes: a point list and a radius list, and the corresponding points with a pixel value of 1 extracted from the binarized image of each layer are filled into the point list.
  • S3200 Search the circles sliced in each layer, compare the number of pixels in the search engine list of each layer and the radius of the circle, and find the center point that meets the conditions, including:
  • step D) setting the number threshold of the pixel points in the point list of each layer of slices is N threshold 1 , and the radius threshold is R threshold 1 , and sequentially from the top layer, the process of step E to step 1 is carried out to each layer slice;
  • N k > N threshold 1 then re-determine the center of the circle, take the closest point between the center of the circle in the k-1 slice and the end point D in the point list as the center O k , go to step I, if not detected If it is a circle, go to step H;
  • the method further includes: filtering the circle center P 5k to generate a new point list, including:
  • step E If the gray value of the center P 5k on the new image from which the lungs, descending aorta, spine, and ribs are removed is less than 0, repeat the process from step E to step I until the radius R 1 ⁇ R threshold 2 is found , and The center of the circle P 5k whose gray value is greater than or equal to 0;
  • the method further includes: filtering the radius R k to generate a new radius list, including:
  • N N k ⁇ N threshold 2 , or N k ⁇ N threshold 2 , L ⁇ L threshold , replace the radius value of the point away from the center P 5k with the average radius value of the remaining points, as R k , replace the radius R k is filled in the radius list, a new radius list is generated, and the points on the centerline of the aorta that meet the conditions are obtained.
  • Lthreshold 8mm.
  • the present application provides a method for picking up points on the central line of the aorta based on CT sequence images, which is a new method for acquiring points on the central line of the aorta, which has the advantages of fast and accurate extraction and fast calculation speed.
  • the center point picking device 400 includes: a search unit 410, a comparison unit 420, and a center point picking unit 430 connected in sequence;
  • the search unit 410 is connected to the binarization device 300, using To establish a search engine list for each layer of slices in the binarized image group, and search for the circle of each layer of slices;
  • the comparison unit 420 is used to compare the number of pixels and the radius of the circle in the search engine list of each layer; the center of the circle
  • the point picking unit 430 is used to find the center point that meets the conditions from the slices of each layer. If the center point that meets the conditions cannot be found, it searches for the center point of the slice of the next layer.
  • the present application provides a computer storage medium, and when the computer program is executed by a processor, the above-mentioned method for picking up a point on the central line of the aorta based on a CT sequence image is implemented.
  • aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, various aspects of the present invention may be embodied in the form of an entirely hardware implementation, an entirely software implementation (including firmware, resident software, microcode, etc.), or a combination of hardware and software aspects, It may be collectively referred to herein as a "circuit,” "module,” or “system.” Furthermore, in some embodiments, various aspects of the present invention may also be implemented in the form of a computer program product on one or more computer-readable media having computer-readable program code embodied thereon. Implementation of the method and/or system of embodiments of the present invention may involve performing or completing selected tasks manually, automatically, or a combination thereof.
  • a data processor such as a computing platform for executing a plurality of instructions.
  • the data processor includes volatile storage for storing instructions and/or data and/or non-volatile storage for storing instructions and/or data, such as a magnetic hard disk and/or a Move media.
  • a network connection is also provided.
  • a display and/or user input device such as a keyboard or mouse, is optionally also provided.
  • the computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium.
  • the computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or a combination of any of the above. More specific examples (non-exhaustive list) of computer-readable storage media would include the following:
  • a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.
  • a computer-readable signal medium may include a propagated data signal in baseband or as part of a carrier wave, with computer-readable program code embodied thereon. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.
  • a computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device .
  • Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
  • computer program code for performing operations for various aspects of the invention may be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, Smalltalk, C++, and conventional procedural programming languages, such as The "C" programming language or similar programming language.
  • the program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server.
  • the remote computer may be connected to the user's computer through any kind of network - including a local area network (LAN) or a wide area network (WAN) - or may be connected to an external computer (eg using an Internet service provider via Internet connection).
  • LAN local area network
  • WAN wide area network
  • These computer program instructions can also be stored on a computer-readable medium, the instructions cause a computer, other programmable data processing apparatus, or other device to operate in a particular manner, whereby the instructions stored on the computer-readable medium produce a An article of manufacture of instructions implementing the functions/acts specified in one or more blocks of the flowcharts and/or block diagrams.
  • Computer program instructions can also be loaded on a computer (eg, a coronary artery analysis system) or other programmable data processing device to cause a series of operational steps to be performed on the computer, other programmable data processing device or other device to produce a computer-implemented process , such that instructions executing on a computer, other programmable apparatus, or other device provide a process for implementing the functions/acts specified in the flowchart and/or one or more block diagram blocks.
  • a computer eg, a coronary artery analysis system
  • other programmable data processing device to produce a computer-implemented process , such that instructions executing on a computer, other programmable apparatus, or other device provide a process for implementing the functions/acts specified in the flowchart and/or one or more block diagram blocks.

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Abstract

L'invention concerne un procédé et un système d'extraction d'un point sur une ligne centrale d'une aorte sur la base d'une image de séquence de tomodensitométrie. Le procédé comprend les étapes consistant à : démarrer un découpage en couches à partir de la couche supérieure d'une image de tomodensitométrie pour obtenir un groupe d'images bidimensionnelles ; binariser le groupe d'images bidimensionnelles pour obtenir un groupe d'images binarisé ; et obtenir N ≤ Nseuil 1 et R = Rseuil 1 ± m à partir d'une tranche de chaque couche dans le groupe d'images binarisé, N représentant le nombre de points de pixel, et détecter un cercle dans une tranche d'une k-ième couche, et prendre le centre du cercle en tant que centre de cercle P5k et le rayon du cercle correspondant au centre de cercle P5k en tant que Rk. L'invention concerne un procédé d'extraction d'un point sur une ligne centrale d'une aorte sur la base d'une image de séquence de tomodensitométrie. Le procédé est un nouveau procédé d'acquisition d'un point sur une ligne centrale d'une aorte, et présente comme avantages une extraction rapide et précise et une vitesse de calcul rapide.
PCT/CN2020/110231 2020-06-29 2020-08-20 Procédé et système d'extraction de point sur une ligne centrale d'aorte sur la base d'une image de séquence de tomodensitométrie WO2022000734A1 (fr)

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CN202010606963.1A CN111815587A (zh) 2020-06-29 2020-06-29 基于ct序列图像拾取主动脉中心线上的点的方法和系统
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Publication number Priority date Publication date Assignee Title
CN115769252A (zh) * 2020-06-29 2023-03-07 苏州润迈德医疗科技有限公司 基于深度学习获取主动脉的方法和存储介质
CN113096141B (zh) * 2021-04-19 2022-01-11 推想医疗科技股份有限公司 冠状动脉分割方法以及冠状动脉分割装置

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20040171932A1 (en) * 2002-11-27 2004-09-02 Raghav Raman Quantification of aortoiliac endoluminal irregularity
CN105809696A (zh) * 2016-03-11 2016-07-27 中国矿业大学(北京) 序列ct图中肾上腺自动定位分割方法
CN105913432A (zh) * 2016-04-12 2016-08-31 妙智科技（深圳）有限公司 基于ct序列图像的主动脉提取方法及装置
CN109658406A (zh) * 2018-12-25 2019-04-19 广州天鹏计算机科技有限公司 血管图像的识别方法、装置、计算机设备和存储介质
CN110338830A (zh) * 2019-07-30 2019-10-18 赛诺威盛科技（北京）有限公司 自动提取cta影像中头颈血管中心路径的方法
CN110458847A (zh) * 2019-07-05 2019-11-15 心医国际数字医疗系统(大连)有限公司 基于cta影像的自动冠脉分割及中心线提取方法
CN111815586A (zh) * 2020-06-29 2020-10-23 苏州润心医疗器械有限公司 基于ct图像获取左心房、左心室的连通域的方法和系统
CN111815589A (zh) * 2020-06-29 2020-10-23 苏州润心医疗器械有限公司 基于ct序列图像获取无干扰冠脉树图像的方法和系统
CN111815583A (zh) * 2020-06-29 2020-10-23 苏州润心医疗器械有限公司 基于ct序列图像获取主动脉中心线的方法和系统
CN111815585A (zh) * 2020-06-29 2020-10-23 苏州润心医疗器械有限公司 基于ct序列图像获取冠脉树和冠脉入口点的方法和系统

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20040171932A1 (en) * 2002-11-27 2004-09-02 Raghav Raman Quantification of aortoiliac endoluminal irregularity
CN105809696A (zh) * 2016-03-11 2016-07-27 中国矿业大学(北京) 序列ct图中肾上腺自动定位分割方法
CN105913432A (zh) * 2016-04-12 2016-08-31 妙智科技（深圳）有限公司 基于ct序列图像的主动脉提取方法及装置
CN109658406A (zh) * 2018-12-25 2019-04-19 广州天鹏计算机科技有限公司 血管图像的识别方法、装置、计算机设备和存储介质
CN110458847A (zh) * 2019-07-05 2019-11-15 心医国际数字医疗系统(大连)有限公司 基于cta影像的自动冠脉分割及中心线提取方法
CN110338830A (zh) * 2019-07-30 2019-10-18 赛诺威盛科技（北京）有限公司 自动提取cta影像中头颈血管中心路径的方法
CN111815586A (zh) * 2020-06-29 2020-10-23 苏州润心医疗器械有限公司 基于ct图像获取左心房、左心室的连通域的方法和系统
CN111815589A (zh) * 2020-06-29 2020-10-23 苏州润心医疗器械有限公司 基于ct序列图像获取无干扰冠脉树图像的方法和系统
CN111815583A (zh) * 2020-06-29 2020-10-23 苏州润心医疗器械有限公司 基于ct序列图像获取主动脉中心线的方法和系统
CN111815585A (zh) * 2020-06-29 2020-10-23 苏州润心医疗器械有限公司 基于ct序列图像获取冠脉树和冠脉入口点的方法和系统

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