WO2022000731A1 - 基于ct序列图像获取心脏重心和脊椎重心的方法和系统 - Google Patents

基于ct序列图像获取心脏重心和脊椎重心的方法和系统 Download PDF

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WO2022000731A1
WO2022000731A1 PCT/CN2020/110019 CN2020110019W WO2022000731A1 WO 2022000731 A1 WO2022000731 A1 WO 2022000731A1 CN 2020110019 W CN2020110019 W CN 2020110019W WO 2022000731 A1 WO2022000731 A1 WO 2022000731A1
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gravity
center
heart
dimensional data
spine
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PCT/CN2020/110019
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English (en)
French (fr)
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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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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • G06T7/0012Biomedical image inspection
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00Image enhancement or restoration
    • G06T5/40Image enhancement or restoration using histogram techniques
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/10Segmentation; Edge detection
    • G06T7/136Segmentation; Edge detection involving thresholding
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/10Segmentation; Edge detection
    • G06T7/187Segmentation; Edge detection involving region growing; involving region merging; involving connected component labelling
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/60Analysis of geometric attributes
    • G06T7/66Analysis of geometric attributes of image moments or centre of gravity
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2200/00Indexing scheme for image data processing or generation, in general
    • G06T2200/04Indexing scheme for image data processing or generation, in general involving 3D image data
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10072Tomographic images
    • G06T2207/10081Computed x-ray tomography [CT]
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30004Biomedical image processing
    • G06T2207/30008Bone
    • G06T2207/30012Spine; Backbone
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30004Biomedical image processing
    • G06T2207/30048Heart; Cardiac

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  • the present invention relates to the technical field of coronary medicine, in particular to a method and system for acquiring the center of gravity of the heart and the center of gravity of the spine 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 obtaining the center of gravity of the heart and the spine 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 present application provides a method for obtaining the center of gravity of the heart and the center of gravity of the spine based on CT sequence images, including:
  • the center of gravity of the heart and the center of gravity of the spine are obtained.
  • the above-mentioned method for obtaining the center of gravity of the heart and the center of gravity of the spine based on the CT sequence image includes:
  • CT three-dimensional data is obtained from the two-dimensional data.
  • the above-mentioned method for obtaining the center of gravity of the heart and the center of gravity of the spine based on CT sequence images includes:
  • the calculated volume ratio of each region of the grayscale histogram to the total region is compared with the grayscale value volume ratio threshold to obtain the heart.
  • Methods for center of gravity and spine center of gravity include:
  • b represents a constant, 0.4 ⁇ b ⁇ 1;
  • a a constant, 0 ⁇ a ⁇ 0.1.
  • the present application provides a system for obtaining the center of gravity of the heart and the center of gravity of the spine based on CT sequence images, which is used for the above-mentioned method for obtaining the center of gravity of the heart and the center of gravity of the spine based on CT sequence images, including: CT data acquisition devices connected to each other and center of gravity extraction device;
  • the CT data acquisition device is used to acquire three-dimensional data of CT sequence images
  • the center of gravity extraction device is connected to the CT data acquisition device, and is used for acquiring the center of gravity of the heart and the center of gravity of the spine according to the three-dimensional data.
  • the CT data acquisition device includes: a picture collector, a two-dimensional data extraction device, and a three-dimensional data synthesis device connected in sequence;
  • the picture collector is used to obtain a plurality of CT two-dimensional pictures
  • the two-dimensional data extraction device is used to obtain two-dimensional data of the CT two-dimensional image
  • the three-dimensional data synthesis device is used for obtaining CT three-dimensional data according to the two-dimensional data.
  • the center of gravity extraction device includes: a grayscale histogram unit and a center of gravity extraction unit connected in turn;
  • the grayscale histogram unit is connected to the two-dimensional data extraction device, and is used for drawing a grayscale histogram of the CT image according to the CT two-dimensional data;
  • the centroid extraction unit is used for obtaining the heart centroid according to the volume ratio of each area to the total area of the grayscale histogram.
  • the center of gravity extraction unit includes: a gray value volume extraction structure, a gray value volume calculation structure, and a center of gravity extraction structure of each region connected in sequence;
  • the grayscale value volume extraction structure of each region is connected to the grayscale histogram unit, and is used to sequentially acquire points M to M-1 points along the direction from the end point M to the origin O of the grayscale histogram, and M Point to point M-2 until the volume of each gray value area from point M to point O is obtained;
  • the gray value volume calculation structure is used to obtain the volume ratio V of the volume of each gray value region to the total region from point M to point O;
  • the present application provides a computer storage medium, when the computer program is executed by the processor, the above-mentioned method for obtaining the center of gravity of the heart and the center of gravity of the spine based on CT sequence images is implemented.
  • This application provides a method for obtaining the center of gravity of the heart and the center of gravity of the spine based on CT sequence images, which is a new method for obtaining the center of gravity of the heart and the spine, and has the advantages of fast and accurate extraction and fast calculation speed.
  • Fig. 1 is the flow chart of the method for obtaining the center of gravity of the heart and the center of gravity of the spine based on CT sequence images of the present application;
  • Fig. 2 is the flow chart of S1000 of this application.
  • Fig. 3 is the flow chart of S2000 of this application.
  • FIG. 5 is a structural block diagram of the system for obtaining the center of gravity of the heart and the center of gravity of the spine based on CT sequence images of the present application;
  • FIG. 6 is another structural block diagram of the system for obtaining the center of gravity of the heart and spine based on CT sequence images of the present application;
  • CT data acquisition device 100 picture collector 110 , 2D data extraction device 120 , 3D data synthesis device 130 , gravity center extraction device 200 , gray histogram unit 210 , gravity center extraction unit 220 , and volume extraction structure 221 for gray value of each region , the gray value volume calculation structure 222 , and the center of gravity extraction structure 223 .
  • 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 obtaining the center of gravity of the heart and the center of gravity of the spine based on CT sequence images, as shown in FIG. 1 , including:
  • S2200 calculate the volume ratio of each area of the grayscale histogram to the total area, compare it with the grayscale value volume ratio threshold, and obtain the center of gravity of the heart and the center of gravity of the spine, as shown in Figure 4, including:
  • V pick up the starting point corresponding to the gray value area, project the starting point on the CT three-dimensional image, obtain a three-dimensional image of the bone area, and pick up the physical center of gravity of the three-dimensional image of the bone area , which is the spine center of gravity P 1 ;
  • a represents a constant, 0 ⁇ a ⁇ 0.1.
  • a 0.005.
  • the present application provides a method for obtaining the center of gravity of the heart and the center of gravity of the spine based on CT sequence images, which is a new method for obtaining the center of gravity of the heart and the spine, and has the advantages of fast and accurate extraction and fast calculation speed.
  • the present application provides a system for obtaining the center of gravity of the heart and the center of gravity of the spine based on CT sequence images, which is used for the above-mentioned method for obtaining the center of gravity of the heart and the center of gravity of the spine based on CT sequence images, including: interconnected CT data acquisition The device 100 and the center of gravity extraction device 200; the CT data acquisition device 100 is used to acquire three-dimensional data of CT sequence images;
  • the CT data acquisition device 100 includes: a picture collector 110 , a two-dimensional data extraction device 120 , and a three-dimensional data synthesis device 130 connected in sequence; the picture collector 110 is used for acquiring multiple two-dimensional CT pictures; the two-dimensional data extraction device 120 is used to obtain the two-dimensional data of the CT two-dimensional pictures; the three-dimensional data synthesis device 130 is used to obtain the CT three-dimensional data according to the two-dimensional data.
  • the centroid extraction device 200 includes: a grayscale histogram unit 210 and a centroid extraction unit 220 connected in sequence; the grayscale histogram unit 210 is connected to the two-dimensional data extraction device 120 , is used to draw the grayscale histogram of the CT image according to the CT two-dimensional data; the centroid extraction unit 220 is used to obtain the heart centroid and the spine centroid according to the volume ratio of each area to the total area of the grayscale histogram.
  • the center of gravity extraction unit 220 includes: a gray value volume extraction structure 221 , a gray value volume calculation structure 222 and a center of gravity extraction structure 223 connected in sequence;
  • the value volume extraction structure 221 is connected to the grayscale histogram unit 210, and is used for sequentially acquiring points M to M-1, and M to M-2 along the direction from the end point M to the origin O of the grayscale histogram, Until the volume of each gray value area from point M to point O is obtained;
  • the gray value volume calculation structure 222 is used to obtain the volume ratio V of each gray value area to the total area from point M to point O;
  • the physical center of gravity of the image is the center of gravity P 2 of the heart;
  • the present application provides a computer storage medium, and when the computer program is executed by a processor, the above-mentioned method for acquiring the center of gravity of the heart and the center of gravity of the spine based on CT sequence images 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

本申请提供了一种基于CT序列图像获取心脏重心和脊椎重心的方法和系统,方法包括:获取CT序列图像的三维数据;根据所述三维数据和设定的灰度值体积占比阈值,获取心脏重心和脊椎重心。本申请是一种获取心脏、脊椎重心的新方法,具有提取快速、精准的优点,计算速度快。

Description

基于CT序列图像获取心脏重心和脊椎重心的方法和系统 技术领域
本发明涉及冠状动脉医学技术领域,特别是涉及基于CT序列图像获取心脏重心和脊椎重心的方法和系统。
背景技术
心血管疾病是工业化世界中的死亡的首要原因。主要形式的心血管疾病由脂肪物质在供应心脏、大脑、肾脏和下肢的动脉的内组织层中的慢性积聚引起。进行性冠状动脉疾病限制到心脏的血流。由于缺少通过当前的非侵入式测试提供的准确信息,许多患者需要侵入式导管流程来评价冠脉血流。因此,存在对于量化人类冠状动脉中的血流以评价可能的冠状动脉疾病的功能意义的非侵入式方法的需求。对动脉容量的可靠评价因此对于解决患者需求的处置规划将是重要的。最近的研究已经证明,血流动力学特性,诸如血流储备分数(FFR),是确定针对具有动脉疾病的患者的最佳处置的重要指示器。对血流储备分数的常规评价使用侵入式导管插入术来直接测量血流特性,诸如压力和流速。然而,这些侵入式测量技术对患者存在风险,并且对健康护理系统可以导致显著的成本。
计算机断层摄影动脉血管造影是一种用于对动脉血管进行可视化的计算机断层摄影技术。出于该目的,X射线的射束从辐射源穿过患者的身体中的感兴趣区域以获得投影图像。
由于现有技术中的CT数据无法获得心脏、脊椎的重心或者获得心脏、脊椎的重心的方法较复杂,导致运算量很大,且存在运算速度慢,运算不准确的问题。
发明内容
本发明提供了一种基于CT序列图像获取心脏重心和脊椎重心的方法和系统,以解决现有技术中的CT数据无法获得心脏、脊椎的重心或者获得心脏、脊椎的重心的方法较复杂的问题。
为实现上述目的,第一方面,本申请提供了一种基于CT序列图像获取心脏重心和脊椎重心的方法,包括:
获取CT序列图像的三维数据;
根据所述三维数据和设定的灰度值体积占比阈值,获取心脏重心和脊椎重心。
可选地,上述的基于CT序列图像获取心脏重心和脊椎重心的方法,获取CT序列图像的三维数据的方法包括:
获取多幅CT二维图片;
获取所述CT二维图片的二维数据;
根据所述二维数据获得CT三维数据。
可选地,上述的基于CT序列图像获取心脏重心和脊椎重心的方法,所述根据所述三维数据和设定的灰度值体积占比阈值,获取心脏重心和脊椎重心的方法包括:
根据所述CT二维数据,绘制所述CT图像的灰度直方图;
计算灰度直方图各区域与总区域的体积比,与所述灰度值体积占比阈值进行比较,获得心脏重心和脊椎重心。
可选地,上述的基于CT序列图像获取心脏重心和脊椎重心的方法,所述计算灰度直方图各区域与总区域的体积比,与所述灰度值体积占比阈值进行比较,获得心脏重心和脊椎重心的方法包括:
沿着所述灰度直方图的终点M至原点O方向,依次获取M点至M-1点,M点至M-2点,直至获取到M点至O点的各灰度值区域的体积;
获取各灰度值区域的体积与M点至O点的总区域的体积占比V;
如果V=b,则拾取所述灰度值区域对应的起始点,将所述起始点投射到所述CT三维图像上,获取心脏区域三维图像,拾取所述心脏区域三维图像的物理重心,即为心脏重心P 2
其中,b表示常数,0.4<b<1;
如果V=a,则拾取所述灰度值区域对应的起始点,将所述起始点投射到所述CT三维图像上,获取骨头区域三维图像,拾取所述骨头区域三维图像的物理重心,即为脊椎重心P 1
其中,a表示常数,0<a<0.1。
可选地,上述的基于CT序列图像获取心脏重心和脊椎重心的方法,所述b=0.6;a=0.005。
第二方面,本申请提供了一种基于CT序列图像获取心脏重心和脊椎重心的系统,用于上述的基于CT序列图像获取心脏重心和脊椎重心的方法,包括:相互连接的CT数据获取装置和重心提取装置;
所述CT数据获取装置,用于获取CT序列图像的三维数据;
所述重心提取装置,与所述CT数据获取装置连接,用于根据所述三维数据获取心脏重心和脊椎重心。
可选地,上述的基于CT序列图像获取心脏重心和脊椎重心的系统,所述CT数据获取装置包括:依次连接的图片采集器、二维数据提取装置、三维数据合成装置;
所述图片采集器用于获取多幅CT二维图片;
所述二维数据提取装置用于获取所述CT二维图片的二维数据;
所述三维数据合成装置用于根据所述二维数据获得CT三维数据。
可选地,上述的基于CT序列图像获取心脏重心和脊椎重心的系统,所述 重心提取装置包括:依次连接的灰度直方图单元和重心提取单元;
所述灰度直方图单元,与所述二维数据提取装置连接,用于根据所述CT二维数据,绘制所述CT图像的灰度直方图;
所述重心提取单元,用于根据灰度直方图各区域与总区域的体积比获得心脏重心。
可选地,上述的基于CT序列图像获取心脏重心和脊椎重心的系统,所述重心提取单元包括:依次连接的各区域灰度值体积提取结构、灰度值体积计算结构和重心提取结构;
所述各区域灰度值体积提取结构,与所述灰度直方图单元连接,用于沿着所述灰度直方图的终点M至原点O方向,依次获取M点至M-1点,M点至M-2点,直至获取到M点至O点的各灰度值区域的体积;
所述灰度值体积计算结构,用于获取各灰度值区域的体积与M点至O点的总区域的体积占比V;
所述重心提取结构,用于根据如果V=b,则拾取所述灰度值区域对应的起始点,将所述起始点投射到所述CT三维图像上,获取心脏区域三维图像,拾取所述心脏区域三维图像的物理重心,即为心脏重心P 2;如果V=a,则为脊椎重心,其中,b表示常数,0.4<b<1,0<a<0.1。
第三方面,本申请提供了一种计算机存储介质,计算机程序被处理器执行时实现上述的基于CT序列图像获取心脏重心和脊椎重心的方法。
本申请实施例提供的方案带来的有益效果至少包括:
本申请提供了基于CT序列图像获取心脏重心和脊椎重心的方法,是一种获取心脏、脊椎重心的新方法,具有提取快速、精准的优点,计算速度快。
附图说明
此处所说明的附图用来提供对本发明的进一步理解,构成本发明的一部 分,本发明的示意性实施例及其说明用于解释本发明,并不构成对本发明的不当限定。在附图中:
图1为本申请的基于CT序列图像获取心脏重心和脊椎重心的方法的流程图;
图2为本申请的S1000的流程图;
图3为本申请的S2000的流程图;
图4为本申请的S2200的流程图;
图5为本申请的基于CT序列图像获取心脏重心和脊椎重心的系统的结构框图;
图6为本申请的基于CT序列图像获取心脏重心脊椎重心的系统的另一结构框图;
下面对附图标记进行说明:
CT数据获取装置100,图片采集器110,二维数据提取装置120,三维数据合成装置130,重心提取装置200,灰度直方图单元210,重心提取单元220,各区域灰度值体积提取结构221,灰度值体积计算结构222,重心提取结构223。
具体实施方式
为使本发明的目的、技术方案和优点更加清楚,下面将结合本发明具体实施例及相应的附图对本发明技术方案进行清楚、完整地描述。显然,所描述的实施例仅是本发明一部分实施例,而不是全部的实施例。基于本发明中的实施例,本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例,都属于本发明保护的范围。
以下将以图式揭露本发明的多个实施方式,为明确说明起见,许多实务上的细节将在以下叙述中一并说明。然而,应了解到,这些实务上的细节不应用以限制本发明。也就是说,在本发明的部分实施方式中,这些实务上的细节是非必要的。此外,为简化图式起见,一些习知惯用的结构与组件在图式中将以 简单的示意的方式绘示之。
现有技术中的CT数据不做筛选,导致运算量很大,且存在运算速度慢,运算不准确的问题。
实施例1:
为了解决上述问题,本申请提供了一种基于CT序列图像获取心脏重心和脊椎重心的方法,如图1所示,包括:
S1000,获取CT序列图像的三维数据,如图2所示,包括:
S1100,获取多幅CT二维图片;
S1120,获取所述CT二维图片的二维数据;
S1130,根据所述二维数据获得CT三维数据。
S2000,根据所述三维数据和设定的灰度值体积占比阈值,获取心脏重心和脊椎重心,如图3所示,包括:
S2100,绘制CT图像的灰度直方图;
S2200,计算灰度直方图各区域与总区域的体积比,与所述灰度值体积占比阈值进行比较,获得心脏重心和脊椎重心,如图4所示,包括:
S2210,沿着灰度直方图的终点M至原点O方向,依次获取M点至M-1点,M点至M-2点,直至获取到M点至O点的各灰度值区域的体积;
S2220,获取各灰度值区域的体积与M点至O点的总区域的体积占比V;
S2230,如果V=b,则拾取灰度值区域对应的起始点,将起始点投射到CT三维图像上,获取心脏区域三维图像,拾取心脏区域三维图像的物理重心,即为心脏重心P 2;其中,b表示常数,0.4<b<1。优选地,b=0.6。
S2240,如果V=a,则拾取所述灰度值区域对应的起始点,将所述起始点投射到所述CT三维图像上,获取骨头区域三维图像,拾取所述骨头区域三维图像的物理重心,即为脊椎重心P 1;其中,a表示常数,0<a<0.1。优选地,a=0.005。
本申请提供了基于CT序列图像获取心脏重心和脊椎重心的方法,是一种获取心脏和脊椎重心的新方法,具有提取快速、精准的优点,计算速度快。
a=0.005,b=0.6是根据医学知识,以及经过大量的实验计算获得的,是一种创造性的劳动,具有突出的实质性特点。
实施例2:
如图5所示,本申请提供了一种基于CT序列图像获取心脏重心和脊椎重心的系统,用于上述的基于CT序列图像获取心脏重心和脊椎重心的方法,包括:相互连接的CT数据获取装置100和重心提取装置200;CT数据获取装置100用于获取CT序列图像的三维数据;重心提取装置200与CT数据获取装置100连接,用于根据三维数据获取心脏重心和脊椎重心。
如图6所示,本申请的一个实施例中,CT数据获取装置100包括:依次连接的图片采集器110、二维数据提取装置120、三维数据合成装置130;图片采集器110用于获取多幅CT二维图片;二维数据提取装置120用于获取所述CT二维图片的二维数据;三维数据合成装置130用于根据所述二维数据获得CT三维数据。
如图6所示,本申请的一个实施例中,重心提取装置200包括:依次连接的灰度直方图单元210和重心提取单元220;灰度直方图单元210,与二维数据提取装置120连接,用于根据CT二维数据,绘制所述CT图像的灰度直方图;重心提取单元220,用于根据灰度直方图各区域与总区域的体积比获得心脏重心和脊椎重心。
如图6所示,本申请的一个实施例中,重心提取单元220包括:依次连接的各区域灰度值体积提取结构221、灰度值体积计算结构222和重心提取结构223;各区域灰度值体积提取结构221与灰度直方图单元210连接,用于沿着所述灰度直方图的终点M至原点O方向,依次获取M点至M-1点,M点至 M-2点,直至获取到M点至O点的各灰度值区域的体积;灰度值体积计算结构222用于获取各灰度值区域的体积与M点至O点的总区域的体积占比V;重心提取结构223用于根据如果V=b,则拾取所述灰度值区域对应的起始点,将所述起始点投射到所述CT三维图像上,获取心脏区域三维图像,拾取所述心脏区域三维图像的物理重心,即为心脏重心P 2;如果V=a,则为脊椎重心,其中,b表示常数,0.4<b<1,0<a<0.1。
本申请提供了一种计算机存储介质,计算机程序被处理器执行时实现上述的基于CT序列图像获取心脏重心和脊椎重心的方法。
所属技术领域的技术人员知道,本发明的各个方面可以实现为系统、方法或计算机程序产品。因此,本发明的各个方面可以具体实现为以下形式,即:完全的硬件实施方式、完全的软件实施方式(包括固件、驻留软件、微代码等),或硬件和软件方面结合的实施方式,这里可以统称为“电路”、“模块”或“系统”。此外,在一些实施例中,本发明的各个方面还可以实现为在一个或多个计算机可读介质中的计算机程序产品的形式,该计算机可读介质中包含计算机可读的程序代码。本发明的实施例的方法和/或系统的实施方式可以涉及到手动地、自动地或以其组合的方式执行或完成所选任务。
例如,可以将用于执行根据本发明的实施例的所选任务的硬件实现为芯片或电路。作为软件,可以将根据本发明的实施例的所选任务实现为由计算机使用任何适当操作系统执行的多个软件指令。在本发明的示例性实施例中,由数据处理器来执行如本文的根据方法和/或系统的示例性实施例的一个或多个任务,诸如用于执行多个指令的计算平台。可选地,该数据处理器包括用于存储指令和/或数据的易失性储存器和/或用于存储指令和/或数据的非易失性储存器,例如,磁硬盘和/或可移动介质。可选地,也提供了一种网络连接。可选地也提供显示器和/或用户输入设备,诸如键盘或鼠标。
可利用一个或多个计算机可读的任何组合。计算机可读介质可以是计算机可读信号介质或计算机可读存储介质。计算机可读存储介质例如可以是——但不限于——电、磁、光、电磁、红外线、或半导体的系统、装置或器件,或者任意以上的组合。计算机可读存储介质的更具体的例子(非穷举列表)将包括以下各项:
具有一个或多个导线的电连接、便携式计算机盘、硬盘、随机存取存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、光纤、便携式紧凑盘只读存储器(CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。在本文件中,计算机可读存储介质可以是任何包含或存储程序的有形介质,该程序可以被指令执行系统、装置或者器件使用或者与其结合使用。
计算机可读的信号介质可以包括在基带中或者作为载波一部分传播的数据信号,其中承载了计算机可读的程序代码。这种传播的数据信号可以采用多种形式,包括但不限于电磁信号、光信号或上述的任意合适的组合。计算机可读的信号介质还可以是计算机可读存储介质以外的任何计算机可读介质,该计算机可读介质可以发送、传播或者传输用于由指令执行系统、装置或者器件使用或者与其结合使用的程序。
计算机可读介质上包含的程序代码可以用任何适当的介质传输,包括(但不限于)无线、有线、光缆、RF等等,或者上述的任意合适的组合。
例如,可用一个或多个编程语言的任何组合来编写用于执行用于本发明的各方面的操作的计算机程序代码,包括诸如Java、Smalltalk、C++等面向对象编程语言和常规过程编程语言,诸如″C″编程语言或类似编程语言。程序代码可以完全地在用户计算机上执行、部分地在用户计算机上执行、作为一个独立的软件包执行、部分在用户计算机上部分在远程计算机上执行、或者完全在远 程计算机或服务器上执行。在涉及远程计算机的情形中,远程计算机可以通过任意种类的网络--包括局域网(LAN)或广域网(WAN)-连接到用户计算机,或者,可以连接到外部计算机(例如利用因特网服务提供商来通过因特网连接)。
应当理解,流程图和/或框图的每个方框以及流程图和/或框图中各方框的组合,都可以由计算机程序指令实现。这些计算机程序指令可以提供给通用计算机、专用计算机或其它可编程数据处理装置的处理器,从而生产出一种机器,使得这些计算机程序指令在通过计算机或其它可编程数据处理装置的处理器执行时,产生了实现流程图和/或框图中的一个或多个方框中规定的功能/动作的装置。
也可以把这些计算机程序指令存储在计算机可读介质中,这些指令使得计算机、其它可编程数据处理装置、或其它设备以特定方式工作,从而,存储在计算机可读介质中的指令就产生出包括实现流程图和/或框图中的一个或多个方框中规定的功能/动作的指令的制造品(article of manufacture)。
还可将计算机程序指令加载到计算机(例如,冠状动脉分析系统)或其它可编程数据处理设备上以促使在计算机、其它可编程数据处理设备或其它设备上执行一系列操作步骤以产生计算机实现过程,使得在计算机、其它可编程装置或其它设备上执行的指令提供用于实现在流程图和/或一个或多个框图方框中指定的功能/动作的过程。
本发明的以上的具体实例,对本发明的目的、技术方案和有益效果进行了进一步详细说明,所应理解的是,以上仅为本发明的具体实施例而已,并不用于限制本发明,凡在本发明的精神和原则之内,所做的任何修改、等同替换、改进等,均应包含在本发明的保护范围之内。

Claims (10)

  1. 一种基于CT序列图像获取心脏重心和脊椎重心的方法,其特征在于,包括:
    获取CT序列图像的三维数据;
    根据所述三维数据和设定的灰度值体积占比阈值,获取心脏重心和脊椎重心。
  2. 根据权利要求1所述的基于CT序列图像获取心脏重心和脊椎重心的方法,其特征在于,获取CT序列图像的三维数据的方法包括:
    获取多幅CT二维图片;
    获取所述CT二维图片的二维数据;
    根据所述二维数据获得CT三维数据。
  3. 根据权利要求1所述的基于CT序列图像获取心脏重心和脊椎重心的方法,其特征在于,所述根据所述三维数据和设定的灰度值体积占比阈值,获取心脏重心和脊椎重心的方法包括:
    根据所述CT二维数据,绘制所述CT图像的灰度直方图;
    计算灰度直方图各区域与总区域的体积比,与所述灰度值体积占比阈值进行比较,获得心脏重心和脊椎重心。
  4. 根据权利要求3所述的基于CT序列图像获取心脏重心和脊椎重心的方法,其特征在于,所述计算灰度直方图各区域与总区域的体积比,与所述灰度值体积占比阈值进行比较,获得心脏重心和脊椎重心的方法包括:
    沿着所述灰度直方图的终点M至原点O方向,依次获取M点至M-1点,M点至M-2点,直至获取到M点至O点的各灰度值区域的体积;
    获取各灰度值区域的体积与M点至O点的总区域的体积占比V;
    如果V=b,则拾取所述灰度值区域对应的起始点,将所述起始点投射到所 述CT三维图像上,获取心脏区域三维图像,拾取所述心脏区域三维图像的物理重心,即为心脏重心P 2
    其中,b表示常数,0.4<b<1;
    如果V=a,则拾取所述灰度值区域对应的起始点,将所述起始点投射到所述CT三维图像上,获取骨头区域三维图像,拾取所述骨头区域三维图像的物理重心,即为脊椎重心P 1
    其中,a表示常数,0<a<0.1。
  5. 根据权利要求4所述的基于CT序列图像获取心脏重心和脊椎重心的方法,其特征在于,所述b=0.6;所述a=0.005。
  6. 一种基于CT序列图像获取心脏重心和脊椎重心的系统,用于权利要求1~5任一项所述的基于CT序列图像获取心脏重心和脊椎重心的方法,其特征在于,包括:相互连接的CT数据获取装置和重心提取装置;
    所述CT数据获取装置,用于获取CT序列图像的三维数据;
    所述重心提取装置,与所述CT数据获取装置连接,用于根据所述三维数据获取心脏重心和脊椎重心。
  7. 根据权利要求6所述的基于CT序列图像获取心脏重心和脊椎重心的系统,其特征在于,所述CT数据获取装置包括:依次连接的图片采集器、二维数据提取装置、三维数据合成装置;
    所述图片采集器用于获取多幅CT二维图片;
    所述二维数据提取装置用于获取所述CT二维图片的二维数据;
    所述三维数据合成装置用于根据所述二维数据获得CT三维数据。
  8. 根据权利要求7所述的基于CT序列图像获取心脏重心和脊椎重心的系统,其特征在于,所述重心提取装置包括:依次连接的灰度直方图单元和重心提取单元;
    所述灰度直方图单元,与所述二维数据提取装置连接,用于根据所述CT二维数据,绘制所述CT图像的灰度直方图;
    所述重心提取单元,用于根据灰度直方图各区域与总区域的体积比获得心脏重心。
  9. 根据权利要求8所述的基于CT序列图像获取心脏重心和脊椎重心的系统,其特征在于,所述重心提取单元包括:依次连接的各区域灰度值体积提取结构、灰度值体积计算结构和重心提取结构;
    所述各区域灰度值体积提取结构,与所述灰度直方图单元连接,用于沿着所述灰度直方图的终点M至原点O方向,依次获取M点至M-1点,M点至M-2点,直至获取到M点至O点的各灰度值区域的体积;
    所述灰度值体积计算结构,用于获取各灰度值区域的体积与M点至O点的总区域的体积占比V;
    所述重心提取结构,用于根据如果V=b,则拾取所述灰度值区域对应的起始点,将所述起始点投射到所述CT三维图像上,获取心脏区域三维图像,拾取所述心脏区域三维图像的物理重心,即为心脏重心P 2;如果V=a,则为脊椎重心,其中,b表示常数,0.4<b<1,0<a<0.1。
  10. 一种计算机存储介质,其特征在于,计算机程序被处理器执行时实现权利要求1~5任一项所述的基于CT序列图像获取心脏重心和脊椎重心的方法。
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Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105678746A (zh) * 2015-12-30 2016-06-15 上海联影医疗科技有限公司 一种医学图像中肝脏范围的定位方法及装置
CN105741293A (zh) * 2016-01-30 2016-07-06 上海联影医疗科技有限公司 定位医学图像上器官的方法
CN109035203A (zh) * 2018-06-25 2018-12-18 青岛海信医疗设备股份有限公司 医学图像处理方法、装置、设备及存储介质
WO2019178432A1 (en) * 2018-03-15 2019-09-19 The Penn State Research Foundation Method for improved recovery in ultra-tight reservoirs based on diffusion
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
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
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
CN111815588A (zh) * 2020-06-29 2020-10-23 苏州润心医疗器械有限公司 基于ct序列图像获取降主动脉的方法和系统

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105678746A (zh) * 2015-12-30 2016-06-15 上海联影医疗科技有限公司 一种医学图像中肝脏范围的定位方法及装置
CN105741293A (zh) * 2016-01-30 2016-07-06 上海联影医疗科技有限公司 定位医学图像上器官的方法
WO2019178432A1 (en) * 2018-03-15 2019-09-19 The Penn State Research Foundation Method for improved recovery in ultra-tight reservoirs based on diffusion
CN109035203A (zh) * 2018-06-25 2018-12-18 青岛海信医疗设备股份有限公司 医学图像处理方法、装置、设备及存储介质
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
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
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
CN111815588A (zh) * 2020-06-29 2020-10-23 苏州润心医疗器械有限公司 基于ct序列图像获取降主动脉的方法和系统

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