WO2022000728A1

WO2022000728A1 - Method and system for acquiring descending aorta on basis of ct sequence image

Info

Publication number: WO2022000728A1
Application number: PCT/CN2020/109848
Authority: WO
Inventors: 王之元; 冯亮; 刘广志; 陈韵岱
Original assignee: 苏州润迈德医疗科技有限公司
Priority date: 2020-06-29
Filing date: 2020-08-18
Publication date: 2022-01-06
Also published as: CN111815588A; CN111815588B

Abstract

Provided are a method and system for acquiring a descending aorta on the basis of a CT sequence image. The method comprises: acquiring three-dimensional data of a CT sequence image; acquiring the barycenter of a heart and the barycenter of a spine according to the three-dimensional data; filtering out impurity data from a CT three-dimensional image to obtain an image that contains a left atrium, a right atrium and an interference-free coronary artery tree; performing layered slicing to obtain a binary image group; obtaining the center of a circle and the radius of the circle on each slice in the binary image group, so as to generate a center list and a radius list; and making pixel points in the center list and the radius list correspond to the image, so as to obtain the center line of an aorta. In the present application, the barycenter of a heart and the barycenter of a spine are selected firstly, so as to position the locations of the heart and the spine; lung tissue, the descending aorta, the spine and the ribs are then removed from a CT image according to the locations of the heart and the spine; and the center line of the aorta is then extracted from a processed image, such that the calculation amount is reduced, an algorithm is simple, the operation thereof is easy, the calculation speed is high, the design is scientific, and the processing of an image is precise.

Description

Method and system for acquiring descending aorta based on CT sequence images

technical field

The present invention relates to the technical field of coronary medicine, in particular to a method and system for acquiring descending aorta based on CT sequence images.

Background technique

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. Recent studies have demonstrated that 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.

Computed tomography arterial angiography is a computed tomography technique used to visualize arterial blood vessels. For this purpose, 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.

Since the CT data in the prior art is not screened, the amount of computation is large, and the computation speed is slow and the computation is inaccurate.

SUMMARY OF THE INVENTION

The present invention provides a method and system for acquiring descending aorta based on CT sequence images, so as to solve the problem of how to accurately extract the blood vessel centerline.

In order to achieve the above object, in a first aspect, the present application provides a method for acquiring descending aorta based on CT sequence images, including:

Obtain three-dimensional data of CT sequence images;

Obtain the center of gravity of the heart and the center of gravity of the spine according to the three-dimensional data;

An image of the descending aorta is acquired according to the center of gravity of the heart and the center of gravity of the spine.

Optionally, in the above-mentioned method for obtaining the descending aorta based on CT sequence images, the method for obtaining the center of gravity of the heart according to the three-dimensional data includes:

drawing a grayscale histogram of the CT image;

Along the direction from the end point M to the origin point O of the grayscale histogram, sequentially acquire points M to M-1, and M to M-2, until the volume of each gray value region from point M to point O is acquired ;

Obtain the volume ratio V of the volume of each gray value area to the total area from point M to point O;

If V=b, pick 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 heart area, and pick up the physical center of gravity of the three-dimensional image of the heart area, that is, is the center of gravity P ₂ of the heart;

Wherein, b represents a constant, 0.2<b<1.

Optionally, the above-mentioned method for obtaining the descending aorta based on CT sequence images, the method for obtaining the spine center of gravity according to the three-dimensional data includes:

If V=a, pick the starting point corresponding to the gray value area, project the starting point on the CT 3D image, obtain the 3D image of the bone area, and pick up the physical center of gravity of the 3D image of the bone area, that is, is the spine center of gravity P ₁ ;

Among them, a represents a constant, 0<a<0.2.

Optionally, in the above-mentioned method for obtaining descending aorta based on CT sequence images, the method for filtering impurity data from the CT three-dimensional image comprises: removing lung tissue, descending aorta, spine, ribs from the CT three-dimensional image , a fifth image containing the left atrium, left ventricle, and undisturbed coronary tree was obtained.

Optionally, in the above-mentioned method for obtaining descending aorta based on CT sequence images, the method for removing lung tissue according to the CT three-dimensional image includes:

According to medical knowledge and the principle of CT image imaging, set the lung gray threshold Q _lung ;

If the grayscale value in the grayscale histogram is smaller than Q _lung , the image corresponding to the grayscale value is removed to obtain the first image with the lung tissue removed.

Optionally, in the above-mentioned method for obtaining the descending aorta based on CT sequence images, the method for removing the descending aorta according to the CT three-dimensional image includes:

Projecting the center of gravity P _{2 of} the heart onto the first image to obtain the center O _{1 of the} heart;

Setting the descending aorta grayscale threshold Q _Drop , and performing binarization processing on the first image;

The distance from the center O ₁ of the heart and the aorta, and the distance of the heart and the spinal center O ₁ of the drop, obtaining circle corresponding descending aorta.

Optionally, in the above-mentioned method for obtaining descending aorta based on CT sequence images, the method for setting the descending aorta grayscale threshold Q- _drop , and performing binarization processing on the first image includes:

Obtain the pixel point PO whose gray value in the first image is greater than the descending aortic gray threshold Q- _drop , and calculate the average gray value of the pixel point PO

Start layered slicing from the bottom layer of the first image to obtain a first two-dimensional slice image group;

according to

Perform binarization processing on the first image, remove the impurity points in the first image, and obtain a binarized image, where k is a positive integer, and Q _k represents the gray value corresponding to the kth pixel PO , P(k) represents the pixel value corresponding to the kth pixel PO.

Alternatively, the above-described method of acquiring CT image based on the sequence of the descending aorta, the descending according to the distance from the center O ₁ of the heart and aorta, and the distance of the heart and the spinal center O ₁ of the acquired Methods of circle corresponding to the descending aorta include:

Setting the radius threshold of the circle formed by the descending aorta to the heart edge as r _threshold ;

According to the distance between the descending aorta and the heart is smaller than the distance between the spine and the heart, obtain the approximate area of the spine and the approximate area of the descending aorta;

According to the approximate area of the descending aorta, the error pixel points are removed to obtain the image of the descending aorta, which is the circle corresponding to the descending aorta.

Optionally, in the above-mentioned method for obtaining the descending aorta based on CT sequence images, according to the distance between the descending aorta and the heart is smaller than the distance between the spine and the heart, the approximate area of the spine is obtained and The approach to the approximate area of the descending aorta includes:

If the radius r of the circle obtained by the Hough detection algorithm > r _threshold , the circle is the circle corresponding to the spine, and the center and radius of the circle are not recorded, that is, the approximate area of the spine;

If the radius of the circle obtained by the Hough detection algorithm is r≤r _threshold , the circle may be the circle corresponding to the descending aorta, and the center and radius of the circle are recorded, which is the approximate area of the descending aorta.

Optionally, in the above-mentioned method for obtaining the descending aorta based on CT sequence images, according to the approximate area of the descending aorta, the error pixels are removed to obtain the descending aorta image, that is, the descending aorta corresponds to the descending aorta. The circle methods include:

The center and radius of the circle in the approximate area of the descending aorta are screened, and the circle with a large center deviation between adjacent slices is removed, that is, the error pixel points are removed, and a list of seed points of the descending aorta is formed to obtain The image of the descending aorta is the circle corresponding to the descending aorta.

In a second aspect, the present application provides a method for removing descending aorta based on CT sequence images, comprising:

The above-mentioned method for obtaining descending aorta based on CT sequence images;

The descending aorta was removed from the first image to obtain a second image.

Optionally, in the above-mentioned method for removing the descending aorta based on CT sequence images, the method for removing the descending aorta from the first image to obtain the second image includes:

If the number of circle centers in the seed point list is greater than or equal to 3, calculate the average radius of all the seed points

and the mean center point P ₃ ;

Calculate with P ₃ as the center of the circle, with

is the average value of the gray value of all pixel points PO in the circle of radius

Set the parameter a to get the grayscale threshold of the connected domain

where a is a positive number;

Recalculate the center point P _{4 of the} connected domain;

Starting from the bottom layer, calculate the Euclidean distance between _{P 3} and P ₄ on the two-dimensional slice of each layer in turn;

_{If the Euclidean distance between P 3} and P ₄ on the two-dimensional slice of the b-th layer is greater than m, set the pixel value corresponding to the pixel point PO of all the two-dimensional slices of the b-th layer and above to 0, and obtain The images corresponding to the first layer to the b-1th layer are the second image, where b is a positive number greater than or equal to 2, and m≥5;

_{If the Euclidean distance between P 3} and P ₄ on the two-dimensional slice of the b-th layer is less than or equal to m, extract the pixels whose gray value is greater than 0 in the two-dimensional slice of the b-th layer, and set the b-th P layer on the two-dimensional slice of _3:00 to point P _4; the first layer than b + 1 to the pixel values and all the PO pixels corresponding to the two-dimensional slices is 0, to obtain a first layer The image corresponding to the b-th layer is the second image.

In a third aspect, the present application provides a computer storage medium, and when the computer program is executed by a processor, the above-mentioned method for acquiring descending aorta based on CT sequence images is implemented.

In a fourth aspect, the present application provides a system for obtaining a coronary tree based on CT sequence images, including: a CT data acquisition device, a heart gravity center extraction device, a spine gravity center extraction device, and a descending aorta extraction device;

The CT data acquisition device is used to acquire three-dimensional data of CT sequence images;

the cardiac center of gravity extraction device, connected to the CT data acquisition device, for acquiring the cardiac center of gravity according to the three-dimensional data;

The spine gravity center extraction device is connected to the CT data acquisition device, and is used for acquiring the spine gravity center according to the three-dimensional data;

The descending aorta extraction device is connected to the CT data acquisition device, the heart gravity center extraction device, and the spine gravity center extraction device, and is used for obtaining an image including the descending aorta from the CT three-dimensional image.

The beneficial effects brought by the solutions provided in the embodiments of the present application include at least:

The present application provides a method for obtaining the descending aorta based on CT sequence images. By first screening out the center of gravity of the heart and the center of gravity of the spine, locating the positions of the heart and the spine, and then obtaining images of the descending aorta according to the positions of the heart and the spine, reducing the computational cost The algorithm is simple, easy to operate, fast in operation, scientific in design, and accurate in image processing.

Description of drawings

The accompanying drawings described herein are used to provide further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the attached image:

Fig. 1 is the flow chart of the method for obtaining descending aorta based on CT sequence image of the present application;

2 is a flowchart method for obtaining cardiac gravity P ₂ of the present application;

Fig. 3 is the flow chart of the method for removing lung tissue of the present application;

Fig. 4 is the flow chart of the method for obtaining descending aorta of the present application;

5 is a flowchart of S3040 of the application;

6 is a flowchart of S3050 of the application;

FIG. 7 is a flowchart of S3060 of the application;

8 is a block diagram of the system structure of the application for obtaining descending aorta based on CT sequence images;

9 is a schematic structural diagram of a first image of the application;

10 is a schematic structural diagram of the second image of the application;

Reference numerals are explained below:

The CT data acquisition device 100 , the cardiac center of gravity extraction device 200 , the spine gravity center extraction device 300 , and the descending aorta extraction device 400 .

detailed description

In order to make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only some, but not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

Various embodiments of the present invention will be disclosed in the drawings below, and for the sake of clarity, many practical details will be described together in the following description. It should be understood, however, that these practical details should not be used to limit the invention. That is, in some embodiments of the invention, these practical details are unnecessary. In addition, for the purpose of simplifying the drawings, some well-known structures and components will be shown in a simple schematic manner in the drawings.

The CT data in the prior art is not screened, resulting in a large amount of computation, slow computation speed and inaccurate computation.

Example 1:

In order to solve the above problems, the present application provides a method for acquiring descending aorta based on CT sequence images, as shown in FIG. 1 , including:

S1000, acquiring three-dimensional data of CT sequence images, including:

S2000, obtain the center of gravity of the heart and the center of gravity of the spine according to the three-dimensional data;

Method P ₂ (1) shown in Figure 2, obtaining the center of gravity of the heart comprising:

S2100, draw a grayscale histogram of the CT image;

S2200, along the direction from the end point M to the origin point O of the grayscale histogram, sequentially acquire points M to M-1, and M to M-2, until the volume of each gray value region from point M to point O is acquired ;

S2300, obtaining the volume ratio V of the volume of each gray value area to the total area from point M to point O;

S2400, if V=b, pick up the starting point corresponding to the gray value area, project the starting point on the CT three-dimensional image, obtain the three-dimensional image of the heart area, and pick up the physical center of gravity of the three-dimensional image of the heart area, which is the center of gravity P _{2 of} the heart; Wherein, b represents a constant, 0.2<b<1. Preferably, 0<a<0.1, a=0.005 has the best effect.

(2) The method of obtaining the center of gravity of the spine P ₁ comprising:

If V=a, pick the starting point corresponding to the gray value area, project the starting point on the CT three-dimensional image, obtain the 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 ; wherein, a represents a constant, 0<a<0.2. Preferably, 0<a<0.1, a=0.005 has the best effect.

S3000, acquiring an image of the descending aorta according to the center of gravity of the heart and the center of gravity of the spine, including:

1) As shown in Figure 3, a method for removing lung tissue, comprising:

S3010, according to medical knowledge and CT image imaging principle, set the lung gray threshold Q _lung ;

S3020, if the gray value in the gray histogram is smaller than the Q _lung , remove the image corresponding to the gray value to obtain the first image with the lung tissue removed as shown in FIG. 9 . Preferably, Q _lung =-150～-50, and Q _lung =-100 has the best effect.

II) As shown in Figure 4, the method for obtaining the descending aorta includes:

S3030, project the center of gravity P _{2 of the} heart on the first image to obtain the center O _{1 of the} heart;

S3040, disposed down the _descending aorta gradation threshold value Q, the first image binarization process; preferably, Q _down = 200, shown in Figure 5, comprising:

S3041, obtaining the pixel point PO whose gray value in the first image is greater than the lower aortic gray threshold Q _drop , and calculating the average gray value of the pixel point PO;

S3042, starting layered slices from the bottom layer of the first image to obtain a first two-dimensional slice image group;

S3043, according to

Perform binarization processing on the first image, remove the impurity points in the first image, and obtain a binarized image, where k is a positive integer, Q _k represents the gray value corresponding to the kth pixel PO, P(k ) represents the pixel value corresponding to the kth pixel PO. Preferably, Q _{crown 1} =150-220, and Q _{crown 1} =200 has the best effect.

S3050, according to the distance of the descending aorta with the heart of the center O _1, and the distance of the spine and the center O ₁ of the heart, acquisition of the circle corresponding to the descending aorta, as shown in FIG. 6, comprising:

S3051, setting the radius threshold of the circle formed by the descending aorta to the edge of the heart as r _threshold ; preferably, r _threshold =5-15;

S3052, according to the distance between the descending aorta and the heart less than the distance between the spine and the heart, obtain the approximate area of the spine and the approximate area of the descending aorta, including:

(1) If the Hough detection algorithm obtains the radius of the circle r > r _threshold , then this circle is the circle corresponding to the spine, and the center and radius of the circle are not recorded, that is, the approximate area of the spine;

(2) If the radius of the circle obtained by the Hough detection algorithm is r≤r _threshold , the circle may be the circle corresponding to the descending aorta. Record the center and radius of the circle, which is the approximate area of the descending aorta.

S3053, according to the approximate area of the descending aorta, remove the error pixel points to obtain an image of the descending aorta, which is a circle corresponding to the descending aorta, including:

Screen the center and radius of the circle in the approximate area of the descending aorta, and remove the circle with a large center deviation between adjacent slices, that is, remove the error pixel points, form the seed point list of the descending aorta, and obtain the image of the descending aorta. , which is the circle corresponding to the descending aorta.

Example 2:

A method for removing the descending aorta based on CT sequence images, comprising: the above-mentioned method for obtaining the descending aorta, and S3060, removing the descending aorta from the first image to obtain the second image shown in FIG. 10 , as shown in FIG. 7, including:

S3061, if the number of centers in the seed point list is greater than or equal to 3, calculate the average radius of all seed points

and the mean center point P ₃ ;

S3062, the calculation takes P ₃ as the center of the circle, and

Set the parameter a to get the grayscale threshold of the connected domain

where a is a positive number; preferably, a=20-40, and a=30 has the best effect.

S3063, recalculate the center point P _{4 of the} connected domain;

S3064, starting from the bottom layer, sequentially calculate the Euclidean distance between _{P 3} and P _{4 on the two-dimensional slice of each layer;}

S3065, if a two-dimensional slice of layer b P ₃ and P ₄ of the Euclidean distance is greater than m, then the second layer b, and is provided above the pixel values of all pixels corresponding to the two-dimensional slices PO is 0, to give first The image corresponding to layer to layer b-1 is the second image, where b is a positive number greater than or equal to 2, and m≥5;

_{S3066, if the Euclidean distance between P 3} and P ₄ on the two-dimensional slice of the b-th layer is less than or equal to m, extract the pixels whose gray value is greater than 0 in the two-dimensional slice of the b-th layer, and put the two-dimensional slice of the b-th layer _{The P 3} point on the slice is set as the P ₄ point; the pixel value corresponding to the pixel point PO of all the two-dimensional slices of the b+1th layer and above is set to 0, and the images corresponding to the first layer to the bth layer are obtained as second image.

The present application provides a method for obtaining the descending aorta based on CT sequence images, by first screening out the center of gravity of the heart and the center of gravity of the spine, locating the positions of the heart and the spine, and then obtaining the descending aorta from the CT image according to the positions of the heart and the spine, It reduces the amount of calculation, the algorithm is simple, easy to operate, the calculation speed is fast, the design is scientific, and the image processing is accurate.

Example 3:

As shown in FIG. 8 , the present application provides a system for obtaining a coronary tree based on CT sequence images, including: a CT data obtaining device 100 , a heart gravity center extraction device 200 , a spine gravity center extraction device 300 , and a descending aorta extraction device 400 ; The CT data acquisition device 100 is used to acquire three-dimensional data of CT sequence images; the cardiac center of gravity extraction device 200 is connected to the CT data acquisition device 100 for acquiring the cardiac center of gravity according to the three-dimensional data; the spine gravity center extraction device 300 is connected to the CT data acquisition device 100 , It is used to obtain the spine gravity center according to the three-dimensional data; the descending aorta extraction device 400 is connected to the CT data acquisition device 100, the heart gravity center extraction device 200, and the spine gravity center extraction device 300, and is used to obtain an image containing the descending aorta from the CT three-dimensional image.

The present application provides a computer storage medium, and when the computer program is executed by a processor, the above-mentioned method for acquiring descending aorta based on CT sequence images is implemented.

As will be appreciated by one skilled in the art, various 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.

For example, hardware for performing selected tasks according to embodiments of the invention may be implemented as a chip or a circuit. As software, selected tasks according to embodiments of the invention may be implemented as a plurality of software instructions executed by a computer using any suitable operating system. In an exemplary embodiment of the invention, one or more tasks according to exemplary embodiments of a method and/or system as herein are performed by a data processor, such as a computing platform for executing a plurality of instructions. Optionally, 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. Optionally, a network connection is also provided. A display and/or user input device, such as a keyboard or mouse, is optionally also provided.

Any combination of one or more computer readable may be utilized. 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:

Electrical connection with one or more wires, portable computer disk, hard disk, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disk Read only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above. In this document, 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.

For example, 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. In the case of a remote computer, 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).

It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer or other programmable data processing apparatus to produce a machine that causes the computer program instructions when executed by the processor of the computer or other programmable data processing apparatus , resulting in means for implementing the functions/acts specified in one or more blocks of the flowchart and/or block diagrams.

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.

The above specific examples of the present invention further describe the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific embodiments of the present invention, and are not intended to limit the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

A method for obtaining descending aorta based on CT sequence images, comprising:

Obtain three-dimensional data of CT sequence images;

Obtain the center of gravity of the heart and the center of gravity of the spine according to the three-dimensional data;

An image of the descending aorta is acquired according to the center of gravity of the heart and the center of gravity of the spine.
The method for obtaining the descending aorta based on CT sequence images according to claim 1, wherein the method for obtaining the center of gravity of the heart according to the three-dimensional data comprises:

drawing a grayscale histogram of the CT image;

Along the direction from the end point M to the origin point O of the grayscale histogram, sequentially acquire points M to M-1, and M to M-2, until the volume of each gray value region from point M to point O is acquired ;

Obtain the volume ratio V of the volume of each gray value area to the total area from point M to point O;

If V=b, pick 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 heart area, and pick up the physical center of gravity of the three-dimensional image of the heart area, that is, is the center of gravity P 2 of the heart;

Wherein, b represents a constant, 0.2<b<1.
The method for obtaining the descending aorta based on CT sequence images according to claim 2, wherein the method for obtaining the spine center of gravity according to the three-dimensional data comprises:

If V=a, pick the starting point corresponding to the gray value area, project the starting point on the CT 3D image, obtain the 3D image of the bone area, and pick up the physical center of gravity of the 3D image of the bone area, that is, is the spine center of gravity P 1 ;

Among them, a represents a constant, 0<a<0.2.
The method for obtaining the descending aorta based on CT sequence images according to claim 3, wherein the method for obtaining the descending aorta image according to the center of gravity of the heart and the center of gravity of the spine comprises:

Lung tissue, descending aorta, vertebrae, ribs were removed from the CT three-dimensional image, resulting in a fifth image containing the left atrium, left ventricle and undisturbed coronary tree.
The method for obtaining descending aorta based on CT sequence images according to claim 4, wherein the method for removing lung tissue according to the CT three-dimensional image comprises:

According to medical knowledge and the principle of CT image imaging, set the lung gray threshold Q lung ;

If the grayscale value in the grayscale histogram is smaller than Q lung , the image corresponding to the grayscale value is removed to obtain a first image with lung tissue removed.
The method for obtaining the descending aorta based on CT sequence images according to claim 5, wherein the method for removing the descending aorta according to the CT three-dimensional image comprises:

Projecting the center of gravity P 2 of the heart onto the first image to obtain the center O 1 of the heart;

Setting the descending aorta grayscale threshold Q Drop , and performing binarization processing on the first image;

The distance from the center O 1 of the heart and the aorta, and the distance of the heart and the spinal center O 1 of the drop, obtaining circle corresponding descending aorta;

An image of the descending aorta is obtained from the CT image.
The method for obtaining the descending aorta based on CT sequence images according to claim 6, wherein the method for setting the descending aorta grayscale threshold Q Drop , and performing binarization processing on the first image comprises the following steps: :

Obtain the pixel point PO whose gray value in the first image is greater than the descending aortic gray threshold Q- drop , and calculate the average gray value of the pixel point PO

Start layered slicing from the bottom layer of the first image to obtain a first two-dimensional slice image group;

according to
Perform binarization processing on the first image, remove the impurity points in the first image, and obtain a binarized image, where k is a positive integer, and Q k represents the gray value corresponding to the kth pixel PO , P(k) represents the pixel value corresponding to the kth pixel PO.
The sequence of CT image acquisition based on the descending aorta method according to claim 7, characterized in that the distance according to the descending aorta and the center O 1 of the heart, and the heart and the spinal center O 1 of distance, and the method for obtaining the circle corresponding to the descending aorta includes:

Setting the radius threshold of the circle formed by the descending aorta to the heart edge as r threshold ;

According to the distance between the descending aorta and the heart is smaller than the distance between the spine and the heart, obtain the approximate area of the spine and the approximate area of the descending aorta;

According to the approximate area of the descending aorta, the error pixel points are removed to obtain the image of the descending aorta, which is the circle corresponding to the descending aorta.
The method for obtaining the descending aorta based on CT sequence images according to claim 8, wherein the obtaining the descending aorta according to the distance between the descending aorta and the heart is smaller than the distance between the spine and the heart Methods for the approximate area of the spine and the approximate area of the descending aorta include:

If the radius r of the circle obtained by the Hough detection algorithm > r threshold , the circle is the circle corresponding to the spine, and the center and radius of the circle are not recorded, that is, the approximate area of the spine;

If the radius of the circle obtained by the Hough detection algorithm is r≤r threshold , the circle may be the circle corresponding to the descending aorta, and the center and radius of the circle are recorded, which is the approximate area of the descending aorta.
The method for obtaining the descending aorta based on CT sequence images according to claim 9, wherein, according to the approximate area of the descending aorta, removing error pixels to obtain the descending aorta image, that is, the descending aorta image is obtained. The method of describing the circle corresponding to the descending aorta includes:

The center and radius of the circle in the approximate area of the descending aorta are screened, and the circle with a large center deviation between adjacent slices is removed, that is, the error pixel points are removed, and a list of seed points of the descending aorta is formed to obtain Image of the descending aorta.
A method for removing descending aorta based on CT sequence images, comprising:

The method for obtaining descending aorta based on CT sequence images according to any one of claims 1 to 10;

The descending aorta is removed from the first image to obtain a second image.
The method for removing the descending aorta based on CT sequence images according to claim 11, wherein the method for removing the descending aorta from the first image to obtain the second image comprises:

If the number of circle centers in the seed point list is greater than or equal to 3, calculate the average radius of all the seed points
and the mean center point P 3 ;

Calculate with P 3 as the center of the circle, with
is the average value of the gray value of all pixel points PO in the circle of radius
Set the parameter a to get the grayscale threshold of the connected domain
where a is a positive number;

Recalculate the center point P 4 of the connected domain;

Starting from the bottom layer, calculate the Euclidean distance between P 3 and P 4 on the two-dimensional slice of each layer in turn;

If the Euclidean distance between P 3 and P 4 on the two-dimensional slice of the b-th layer is greater than m, set the pixel value corresponding to the pixel point PO of all the two-dimensional slices of the b-th layer and above to 0, and obtain The images corresponding to the first layer to the b-1th layer are the second image, where b is a positive number greater than or equal to 2, and m≥5;

If the Euclidean distance between P 3 and P 4 on the two-dimensional slice of the b-th layer is less than or equal to m, extract the pixels whose gray value is greater than 0 in the two-dimensional slice of the b-th layer, and set the b-th P layer on the two-dimensional slice of 3:00 to point P 4; the first layer than b + 1 to the pixel values and all the PO pixels corresponding to the two-dimensional slices is 0, to obtain a first layer The image corresponding to the b-th layer is the second image.
A computer storage medium, characterized in that, when the computer program is executed by the processor, the method for acquiring the descending aorta based on CT sequence images according to any one of claims 1 to 10 is implemented.
A system for obtaining a descending aorta method based on CT sequence images according to any one of claims 1 to 10, characterized in that it comprises: a CT data acquisition device, a heart gravity center extraction device, a spine gravity center extraction device, and a descending aorta extraction device. Aortic extraction device;

The CT data acquisition device is used to acquire three-dimensional data of CT sequence images;

the cardiac center of gravity extraction device, connected to the CT data acquisition device, for acquiring the cardiac center of gravity according to the three-dimensional data;

The spine gravity center extraction device is connected to the CT data acquisition device, and is used for acquiring the spine gravity center according to the three-dimensional data;

The descending aorta extraction device is connected to the CT data acquisition device, the heart gravity center extraction device, and the spine gravity center extraction device, and is used for obtaining an image including the descending aorta from the CT three-dimensional image.