CN114170378A - Medical equipment, blood vessel and internal plaque three-dimensional reconstruction method and device - Google Patents

Medical equipment, blood vessel and internal plaque three-dimensional reconstruction method and device Download PDF

Info

Publication number
CN114170378A
CN114170378A CN202111425153.7A CN202111425153A CN114170378A CN 114170378 A CN114170378 A CN 114170378A CN 202111425153 A CN202111425153 A CN 202111425153A CN 114170378 A CN114170378 A CN 114170378A
Authority
CN
China
Prior art keywords
blood vessel
plaque
information
contour
image information
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202111425153.7A
Other languages
Chinese (zh)
Inventor
徐辉雄
赵崇克
孙丽萍
李焰驹
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Vinno Technology Suzhou Co Ltd
Original Assignee
Vinno Technology Suzhou Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Vinno Technology Suzhou Co Ltd filed Critical Vinno Technology Suzhou Co Ltd
Priority to CN202111425153.7A priority Critical patent/CN114170378A/en
Publication of CN114170378A publication Critical patent/CN114170378A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00Three dimensional [3D] modelling, e.g. data description of 3D objects
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2200/00Indexing scheme for image data processing or generation, in general
    • G06T2200/08Indexing scheme for image data processing or generation, in general involving all processing steps from image acquisition to 3D model generation

Landscapes

  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Computer Graphics (AREA)
  • Geometry (AREA)
  • Software Systems (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Ultra Sonic Daignosis Equipment (AREA)

Abstract

The invention discloses a medical device, a blood vessel and an internal plaque three-dimensional reconstruction method and a device, wherein the method comprises the following steps: obtaining blood vessel image information of a group of blood vessel radial sections, detecting the blood vessel image information through a blood vessel segmentation model and a plaque segmentation model, and obtaining blood vessel contour information and plaque contour information; three-dimensional modeling is carried out on the blood vessel contour information along the scanning track to generate a blood vessel three-dimensional model; the plaque outline information traverses the blood vessel three-dimensional model to generate the blood vessel three-dimensional model with the plaque, and the three-dimensional structures of the blood vessel and the plaque inside can be clearly drawn by the method and the device, so that doctors can make more accurate judgment, and the medical experience of patients is improved.

Description

Medical equipment, blood vessel and internal plaque three-dimensional reconstruction method and device
Technical Field
The invention relates to the technical field of medical ultrasound, in particular to a medical device, a blood vessel and an internal plaque three-dimensional reconstruction method and a device.
Background
Currently, when scanning a carotid artery, an ultrasonic examination is generally adopted, and whether a stable plaque or an unstable plaque is determined according to the situation of echo, for example, if the echo is low or no echo, the plaque may be an unstable plaque.
However, the determination result is not clear, only a general situation can be given, and the blood lipid check, such as detecting the parameter range of low density lipoprotein, needs to be matched, and even then the whole picture of the plaque can not be clearly reflected, and the searching process is complicated. In addition, general carotid plaque does not need surgery, but severe carotid plaque needs to be evaluated before surgery can be judged, and the evaluation of surgery by doctors is influenced by the unclear ultrasonic examination. And the current operation of the carotid plaque has risks, and is problematic for patients who do not need the operation or who do not need the operation. How to make the display of the carotid plaque clearer and more intuitive helps solve the problems.
Disclosure of Invention
In order to solve the problem that plaque of a blood vessel is not clear and intuitive enough in the prior art, the invention aims to provide a three-dimensional reconstruction method and a three-dimensional reconstruction device for the blood vessel and internal plaque.
In order to achieve the above object, an embodiment of the present invention provides a three-dimensional reconstruction method for a blood vessel and an internal plaque, including the steps of:
obtaining blood vessel image information of a group of blood vessel radial sections, wherein the blood vessel image information is sequentially distributed along a scanning track;
obtaining blood vessel contour information corresponding to each blood vessel image information through a blood vessel segmentation model;
screening the blood vessel contour information based on a scanning track;
obtaining plaque outline information corresponding to each blood vessel image information by passing at least part of the blood vessel image information through a plaque segmentation model;
screening the plaque outline information based on the position relation between the plaque and the blood vessel outline;
taking a group of blood vessel contour information along the scanning direction as input, and performing three-dimensional reconstruction through surface drawing to generate a blood vessel three-dimensional model;
traversing each piece of plaque contour information after screening through the blood vessel three-dimensional model to generate the blood vessel three-dimensional model with the plaque.
As a further improvement of the present invention, the step of "acquiring blood vessel image information of a set of radial sections of a blood vessel" includes:
acquiring a group of original images and length and depth information of the three-dimensional model which are sequentially arranged along a scanning track;
and resampling the original image to obtain blood vessel image information, wherein the blood vessel image information is a group of gray level images.
As a further improvement of the present invention, the step of "acquiring a set of original images, length and depth information of the three-dimensional model sequentially arranged along the scanning trajectory" includes:
scanning parameter information is obtained, wherein the scanning parameter information comprises scanning distance information and scanning depth information;
and calculating the length information and the depth information of the three-dimensional model according to the scanning distance information, the scanning depth information and the number information of the original images.
As a further improvement of the present invention, the step of "resampling the original image to obtain blood vessel image information" includes:
graying and compressing the original image into a resample image, wherein the original image is a group of transverse scanning color images vertical to the extending direction of the blood vessel;
and generating a group of blood vessel image information by a linear interpolation algorithm according to the length information and the depth information by taking the resampled image as a data source.
As a further improvement of the present invention, the step of "obtaining blood vessel contour information corresponding to each piece of blood vessel image information by passing the blood vessel image information through a blood vessel segmentation model" includes:
and detecting the blood vessel image information through a blood vessel segmentation model, replacing pixels of which the gray value is greater than or equal to a preset blood vessel confidence value with a first value, and replacing pixels of which the gray value is less than the preset blood vessel confidence value with a second value to generate blood vessel contour information.
As a further improvement of the present invention, the step of "filtering the blood vessel contour information based on the scanning track" includes:
and if the deviation value of the center point of a certain piece of blood vessel contour information and the blood vessel extension track exceeds a preset blood vessel deviation value, screening out the blood vessel contour information.
As a further improvement of the present invention, the step of "acquiring plaque contour information corresponding to each piece of blood vessel image information by passing at least part of the blood vessel image information through a plaque segmentation model" includes:
and obtaining the plaque contour information corresponding to each blood vessel image information through a plaque segmentation model according to the blood vessel image information corresponding to the screened blood vessel contour information.
As a further improvement of the present invention, the step of obtaining plaque contour information corresponding to each piece of blood vessel image information by passing the blood vessel image information corresponding to the blood vessel contour information after the screening through a plaque segmentation model includes:
detecting the blood vessel image information corresponding to the screened blood vessel contour information through a plaque segmentation model, replacing pixels of which the gray value is greater than or equal to a preset plaque confidence value with a first value, and replacing pixels of which the gray value is smaller than the preset plaque confidence value with a second value to generate plaque contour information.
As a further improvement of the present invention, the step of "filtering the plaque outline information based on a positional relationship between the plaque and the blood vessel outline" includes:
and screening the plaque outline information if the deviation degree of the area with the first value on the certain plaque outline information and the area with the first value in the corresponding blood vessel outline information is larger than a preset plaque deviation value.
As a further improvement of the present invention, the step of performing three-dimensional reconstruction by surface rendering using a set of the blood vessel contour information along the scanning direction as an input to generate a three-dimensional model of the blood vessel includes:
determining a first equivalence surface based on a boundary contour of a first value and a second value in the blood vessel contour information, and generating a closed gray equivalent surface through a mobile cube algorithm, wherein the gray equivalent surface is a three-dimensional model of the blood vessel;
the three-dimensional model of the blood vessel is generated as a first color.
As a further improvement of the present invention, the step of traversing each of the plaque contour information after screening through the blood vessel three-dimensional model to generate a blood vessel three-dimensional model with plaque includes:
determining a second equipartition surface by a boundary contour of a first value and a second value in the plaque contour information in sequence along a scanning track, traversing the second equipartition surface through the blood vessel three-dimensional model, replacing the area of the second equipartition surface with a second color different from the first color, and generating the blood vessel three-dimensional model with the plaque.
In order to achieve one of the above objects, an embodiment of the present invention provides a three-dimensional reconstruction apparatus for blood vessels and internal plaques, including:
the acquisition module is used for acquiring a group of blood vessel image information of a blood vessel radial section, and the plurality of blood vessel image information are sequentially distributed along a scanning track;
the blood vessel contour recognition module is used for acquiring blood vessel contour information corresponding to each piece of blood vessel image information through a blood vessel segmentation model and screening the blood vessel contour information based on a scanning track;
the plaque identification module is used for acquiring plaque contour information corresponding to each blood vessel image information from at least part of the blood vessel image information through a plaque segmentation model, and screening the plaque contour information based on the position relation between plaque and blood vessel contour;
the blood vessel modeling module is used for taking a group of blood vessel contour information along the scanning direction as input, performing three-dimensional reconstruction through surface drawing and generating a blood vessel three-dimensional model;
and the plaque modeling module is used for traversing each piece of plaque contour information after screening through the blood vessel three-dimensional model to generate a blood vessel three-dimensional model with plaque.
To achieve one of the above objects, an embodiment of the present invention provides an electronic device, including:
a storage module storing a computer program;
and the processing module can realize the steps in the blood vessel and internal plaque three-dimensional reconstruction method when executing the computer program.
In order to achieve one of the above objects, an embodiment of the present invention provides a readable storage medium, which stores a computer program, and the computer program can implement the steps of the three-dimensional reconstruction method for blood vessels and internal plaques described above when being executed by a processing module.
Compared with the prior art, the invention has the following beneficial effects: the method and the device can be used for clearly drawing the three-dimensional structures of the blood vessel and the internal plaque, a plurality of longitudinal sections are obtained in an ultrasonic mode, the scanning mode is consistent with the existing scanning mode, the scanning device is particularly suitable for scanning carotid arteries, the bifurcation of internal carotid arteries and external carotid arteries can be clearly shown, the position of carotid sinus can be conveniently found, the specific size of the plaque can be conveniently and accurately measured due to the fact that the scanning device is more direct, a doctor can conveniently make more accurate judgment, and the medical experience of a patient is improved.
Drawings
FIG. 1 is a flow chart of a method for three-dimensional reconstruction of blood vessels and internal plaques in accordance with an embodiment of the present invention;
FIG. 2 is a schematic diagram of an original image of a radial section of a blood vessel according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a vessel contour information according to an embodiment of the present invention;
FIG. 4 is a diagram of plaque contour information in accordance with one embodiment of the present invention;
FIG. 5 is a schematic representation of a three-dimensional model of a vessel with plaque in accordance with an embodiment of the present invention;
fig. 6 is a block diagram of a three-dimensional reconstruction apparatus according to an embodiment of the present invention.
Detailed Description
The present invention will be described in detail below with reference to specific embodiments shown in the drawings. These embodiments are not intended to limit the present invention, and structural, methodological, or functional changes made by those skilled in the art according to these embodiments are included in the scope of the present invention.
It will be understood that terms used herein such as "upper," "above," "lower," "below," and the like, refer to relative positions in space and are used for convenience in description to describe one element or feature's relationship to another element or feature as illustrated in the figures. The spatially relative positional terms may be intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures.
An embodiment of the invention provides medical equipment, a blood vessel and an internal plaque three-dimensional reconstruction method and a device.
Fig. 1 is a three-dimensional reconstruction method of a blood vessel and an internal plaque according to an embodiment of the present application, where the three-dimensional reconstruction method is based on a longitudinal sectional view obtained by an ultrasound scan as a data source, and this embodiment may be described by taking scanning of a carotid artery as an example.
Although the present application provides method operational steps as described in the following embodiments or flowcharts, the method is not limited to the order of execution provided in the embodiments of the present application in which the steps are logically not necessarily causal, based on conventional or non-inventive labor.
Specifically, the method comprises the following steps:
step 101: obtaining blood vessel image information of a group of blood vessel radial sections, wherein the blood vessel image information is sequentially distributed along a scanning track;
step 102: obtaining blood vessel contour information corresponding to each blood vessel image information through a blood vessel segmentation model;
step 103: screening the blood vessel contour information based on a scanning track;
step 104: obtaining plaque outline information corresponding to each blood vessel image information by passing at least part of the blood vessel image information through a plaque segmentation model;
step 105: screening the plaque outline information based on the position relation between the plaque and the blood vessel outline;
step 106: taking a group of blood vessel contour information along the scanning direction as input, and performing three-dimensional reconstruction through surface drawing to generate a blood vessel three-dimensional model;
step 107: traversing each piece of plaque contour information after screening through the blood vessel three-dimensional model to generate the blood vessel three-dimensional model with the plaque.
For step 101, in an implementation manner of the present invention, a group of original images and scanning parameter information sequentially arranged along a scanning track may be obtained, where the original images are a plurality of continuous transverse scanning ultrasound images perpendicular to a carotid artery blood vessel direction, and the scanning parameter information includes scanning distance information and scanning depth information. The original image may be a 32-bit color image of RGBA, or may be a grayscale image, and the grayscale image is input as the original image in fig. 2. The scanning ultrasonic image completely covers the carotid artery of the patient, including the aorta, the bifurcation position, the internal carotid artery and the external carotid artery, so that the full appearance of the carotid artery of the patient is completely presented in the three-dimensional reconstructed three-dimensional model, and particularly the plaque condition in the whole carotid artery is displayed.
After obtaining the original image, resampling the original image to obtain blood vessel image information, wherein the blood vessel image information is a group of gray level images, and the blood vessel image can be compressed to a certain extent to reduce the operation amount.
And calculating the length information and the depth information of the three-dimensional model according to the scanning distance information, the scanning depth information and the number information of the original images.
And generating a group of blood vessel image information by a linear interpolation algorithm according to the length information and the depth information by taking the resampled image as a data source. The data volume of the original image is supplemented in a linear interpolation mode, and the generated three-dimensional model is smoother.
For step 102, the blood vessel image information is detected through a blood vessel segmentation model, pixels of which the gray value is greater than or equal to a preset blood vessel confidence value are replaced with a first value, and pixels of which the gray value is smaller than the preset blood vessel confidence value are replaced with a second value, so that blood vessel contour information is generated.
As shown in fig. 3, the blood vessel contour information can be obtained by determining the possibility that each pixel point in fig. 2 is a blood vessel or is in the blood vessel according to the blood vessel depth learning, and then determining the contour of the blood vessel, where the first value may be 255 and the second value is 0, to distinguish the blood vessel from the original image.
In addition, the blood vessel of fig. 3 may be a common carotid artery, and if the image is above the bifurcation position, the blood vessel may include two blood vessels, namely an internal carotid artery and an external carotid artery, and a cross section gradually changing from one blood vessel to two blood vessels is displayed at the Y-shaped bifurcation position, so that the Y-shaped bifurcation is clearly represented in the final three-dimensional model, and a doctor can conveniently find the bifurcation position.
In step 103, replacing the region with the first value in the blood vessel contour information to be an external rectangle, determining the center point of the external rectangle, further obtaining the center points of a plurality of blood vessel contour information sequentially arranged along the scanning track, fitting a blood vessel extending track according to a least square algorithm, and screening out a certain picture if the deviation value of the center point on the certain picture and the blood vessel extending track exceeds a preset blood vessel deviation value. Through a least square algorithm, curve fitting can be carried out on a plurality of central points in the space, the fitted curve is the extending direction of the blood vessel, the picture where the excessively discrete central points are located is removed, the picture which is consistent with the extending direction of the blood vessel is reserved, and the distortion of a three-dimensional model caused by excessive hand shaking of a doctor during ultrasonic scanning or detection distortion of a blood vessel contour model is avoided.
In addition, when a plurality of connected regions exist in the picture, the number of blood vessels on the picture is determined according to the position of the picture, if the number of the excessively appeared connected regions is larger than the number of the blood vessels, the areas of the circumscribed rectangles of the plurality of connected regions are determined, and the areas of the connected regions are excluded in a smaller mode. For example, only the common carotid artery exists in the graph, but 3 connected regions exist, only the region with the largest area is reserved as the first value, and the pixels of the remaining two connected regions with small areas are replaced by the second value. If there are internal and external carotid arteries on the graph, but five connected regions appear, only two regions with large areas are reserved as the first value, and pixels of other connected regions with areas smaller than the two regions with the largest areas are replaced by the second value.
At least part of the blood vessel image information in step 104 may be the blood vessel image information corresponding to all the blood vessel image information passing through the plaque segmentation model, or may be a part of the blood vessel image information, specifically, the blood vessel image information corresponding to the blood vessel contour information filtered in step 103, so that the computation amount can be reduced.
Detecting the blood vessel image information corresponding to the screened blood vessel contour information through a plaque segmentation model, replacing pixels of which the gray value is greater than or equal to a preset plaque confidence value with a first value, and replacing pixels of which the gray value is smaller than the preset plaque confidence value with a second value to generate plaque contour information.
The plaque outline information is shown in fig. 4, and the probability that each pixel point in fig. 2 is a plaque can be judged according to the plaque depth learning, and then the outline of the plaque is determined, where the first value may be 255 and the second value is 0, so as to distinguish the plaque from the original image.
In step 105, the deviation degree between the region with the first value on the plaque contour information and the region with the first value in the corresponding blood vessel contour information is larger than a preset plaque deviation value, and the picture is screened out.
Theoretically, the plaque determined in step 105 should be completely in the blood vessel determined in step 103, taking fig. 3 and 4 as an example, when the plaque is completely in the blood vessel, the plaque determination is reliable; when the plaque is completely outside the blood vessel, judging that a problem exists at the moment, and removing the picture; when the plaque is not completely in the blood vessel, judging according to a preset plaque deviation value, and adjusting the fineness of judgment of plaques with different sizes according to different required precisions and different sizes of the preset plaque deviation value.
For step 106, the surface rendering may adopt a plurality of algorithms, such as a marching cube algorithm, a first equivalence surface is determined based on a boundary contour of a first value and a second value in the blood vessel contour information, and a closed gray-scale equivalence surface is generated by the marching cube algorithm, where the gray-scale equivalence surface is a three-dimensional model of the blood vessel.
The three-dimensional model of the blood vessel is generated in a first color, which may be red.
For step 107, determining a second equipartition surface by sequentially using a boundary contour of a first value and a second value in the plaque contour information along the scanning track, traversing the second equipartition surface through the blood vessel three-dimensional model, replacing an area where the second equipartition surface is located with a second color different from the first color, wherein the second color can be yellow or black; and generating a three-dimensional model of the blood vessel with the plaque, wherein the plaque can also generate a continuous complete closed shape through an algorithm of moving cubes, and the color of the position of the plaque in the blood vessel is replaced to finally present the three-dimensional model of the blood vessel with the plaque, as shown in fig. 5.
The method and the device can be used for clearly drawing the three-dimensional structures of the blood vessel and the internal plaque, a plurality of longitudinal sections are obtained in an ultrasonic mode, the scanning mode is consistent with the existing scanning mode, the scanning device is particularly suitable for scanning carotid arteries, the bifurcation of internal carotid arteries and external carotid arteries can be clearly shown, the position of carotid sinus can be conveniently found, the specific size of the plaque can be conveniently and accurately measured due to the fact that the scanning device is more direct, a doctor can conveniently make more accurate judgment, and the medical experience of a patient is improved.
In an implementation mode, after the blood vessel three-dimensional model with the plaque is obtained, the size and the hardness degree of the blood vessel can be further conveniently calculated, and more specific and accurate data of a doctor can be conveniently given.
The width and height of the plaque can be obtained by calculating the minimum bounding rectangle of the plaque outline; the stenosis rate of the plaque can be calculated by an area method, and the ratio of the area of the plaque outline to the area of the blood vessel outline is calculated; and calculating the hardness degree of the patch according to the proportion that the brightness of the pixel points in the patch outline is greater than a certain threshold value.
As shown in fig. 6, in an embodiment, a three-dimensional reconstruction apparatus for blood vessels and internal plaques is provided, and the three-dimensional reconstruction apparatus may be integrated in a medical device or a server, and specifically may include an acquisition module, a blood vessel contour identification module, a plaque identification module, a blood vessel modeling module, and a plaque modeling module, where the functions of the modules are as follows:
the acquisition module is used for acquiring a group of blood vessel image information of a blood vessel radial section, and the plurality of blood vessel image information are sequentially distributed along a scanning track;
the blood vessel contour recognition module is used for acquiring blood vessel contour information corresponding to each piece of blood vessel image information through a blood vessel segmentation model and screening the blood vessel contour information based on a scanning track;
the plaque identification module is used for acquiring plaque contour information corresponding to each blood vessel image information from at least part of the blood vessel image information through a plaque segmentation model, and screening the plaque contour information based on the position relation between plaque and blood vessel contour;
the blood vessel modeling module is used for taking a group of blood vessel contour information along the scanning direction as input, performing three-dimensional reconstruction through surface drawing and generating a blood vessel three-dimensional model;
and the plaque modeling module is used for traversing each piece of plaque contour information after screening through the blood vessel three-dimensional model to generate a blood vessel three-dimensional model with plaque.
In one embodiment, the obtaining module further comprises a resampling module, and the obtaining module is configured to obtain a set of original images, length of the three-dimensional model, and depth information sequentially arranged along the scanning track;
and the resampling module resamples the original image to obtain blood vessel image information, wherein the blood vessel image information is a group of gray maps.
In one embodiment, the acquisition module is used for acquiring scanning parameter information, wherein the scanning parameter information comprises scanning distance information and scanning depth information;
the three-dimensional reconstruction device also comprises a processing module, wherein the processing module is used for calculating the length information and the depth information of the three-dimensional model according to the scanning distance information, the scanning depth information and the number information of the original images.
In one embodiment, the resampling module is used for graying and compressing the original image into a resampled image, wherein the original image is a group of transverse scanning color images perpendicular to the extending direction of the blood vessel;
and the processing module is used for generating a group of blood vessel image information by a linear interpolation algorithm by taking the resampled image as a data source according to the length information and the depth information.
In one embodiment, the blood vessel contour identification module is configured to detect the blood vessel image information through a blood vessel segmentation model, replace pixels, of which a gray value is greater than or equal to a preset blood vessel confidence value, of the blood vessel image information with a first value, and replace pixels, of which a gray value is less than the preset blood vessel confidence value, with a second value, to generate blood vessel contour information.
In one embodiment, the blood vessel contour identification module is configured to replace an area with a first value in the blood vessel contour information as an external rectangle, determine a center point of the external rectangle, further obtain a plurality of center points of the blood vessel contour information sequentially arranged along a scanning track, fit a blood vessel extension track according to a least square algorithm, and screen out a certain picture if a deviation value between a center point on the certain picture and the blood vessel extension track exceeds a preset blood vessel deviation value.
In one embodiment, the plaque identification module is configured to detect, by a plaque segmentation model, blood vessel image information corresponding to the blood vessel contour information after the screening, replace pixels, of which a gray value is greater than or equal to a preset plaque confidence value, of the blood vessel image information with a first value, and replace pixels, of which a gray value is smaller than the preset plaque confidence value, with a second value, so as to generate plaque contour information.
In one embodiment, the plaque identification module is configured to screen out the image by setting a deviation degree between a region of a first value on the plaque contour information and a corresponding region of the first value in the blood vessel contour information to be greater than a preset plaque deviation value.
In one embodiment, the blood vessel modeling module is used for determining a first equivalent surface based on a boundary contour of a first value and a second value in the blood vessel contour information, and generating a closed gray equivalent surface through a mobile cube algorithm, wherein the gray equivalent surface is a three-dimensional model of the blood vessel; the three-dimensional model of the blood vessel is generated as a first color.
In one embodiment, the plaque modeling module is configured to determine a second equipartition surface from a boundary contour of a first value and a second value in the plaque contour information in sequence along the scanning trajectory, traverse the second equipartition surface through the blood vessel three-dimensional model, replace a region of the second equipartition surface with a second color different from the first color, and generate the blood vessel three-dimensional model with the plaque.
The three-dimensional reconstruction device can be medical equipment, a desktop computer, a notebook computer, a palm computer, a cloud server and other computing equipment. The three-dimensional reconstruction device can include, but is not limited to, a processing module and a storage module. It will be understood by those skilled in the art that the schematic diagram is merely an example of the three-dimensional reconstruction apparatus, and does not constitute a limitation to the terminal device of the three-dimensional reconstruction apparatus, and may include more or less components than those shown in the drawings, or combine some components, or different components, for example, the three-dimensional reconstruction apparatus may further include an input/output device, a network access device, a bus, and the like.
Please refer to the details disclosed in the three-dimensional reconstruction method according to the embodiment of the present invention, for details not disclosed in the three-dimensional reconstruction apparatus according to the embodiment of the present invention.
According to the three-dimensional reconstruction device, the three-dimensional structures of the blood vessel and the internal plaque can be clearly drawn, the plurality of longitudinal sections are obtained in an ultrasonic mode, the scanning mode is consistent with the existing scanning mode, the three-dimensional reconstruction device is particularly suitable for scanning carotid arteries, the bifurcation of internal carotid arteries and external carotid arteries can be clearly displayed, the position of carotid sinus can be conveniently found, the specific size of the plaque can be conveniently and accurately measured due to the fact that the three-dimensional reconstruction device is more direct, a doctor can conveniently make more accurate judgment, and the medical experience of a patient is improved.
The medical device of this embodiment includes: a processing module, a storage module and a computer program stored in the storage module and executable on the processing module, such as the three-dimensional reconstruction method program described above. The processing module, when executing the computer program, implements the steps in the above-described embodiments of the three-dimensional reconstruction method, such as the steps shown in fig. 1.
In addition, the present invention further provides an electronic device, which includes a storage module and a processing module, and when the processing module executes the computer program, the processing module may implement the steps in the three-dimensional reconstruction method for a medical device, that is, implement the steps in any one of the technical solutions of the three-dimensional reconstruction method for a medical device.
The electronic device may be a part integrated in the medical device, or a local terminal device, or may be a part of the cloud server.
The Processing module may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, a discrete hardware component, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The processing module is a control center of the medical equipment and is connected with each part of the whole medical equipment by various interfaces and lines.
The storage module can be used for storing the computer program and/or the module, and the processing module realizes various functions of the medical device by running or executing the computer program and/or the module stored in the storage module and calling data stored in the storage module. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data created according to the use of the cellular phone such as audio data, a phonebook, etc.), and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Illustratively, the computer program may be partitioned into one or more modules/units that are stored in the memory module and executed by the processing module to implement the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program in the medical device.
Further, an embodiment of the present invention provides a readable storage medium, which stores a computer program, and the computer program, when being executed by a processing module, can implement the steps in the three-dimensional reconstruction method of the medical device, that is, implement the steps in any one of the above three-dimensional reconstruction methods.
The integrated module of the three-dimensional reconstruction apparatus may be stored in a computer-readable storage medium if it is implemented in the form of a software functional unit and sold or used as a separate product. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented.
Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, diskettes, removable hard disks, magnetic disks, optical disks, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution media, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
It should be understood that although the present description refers to embodiments, not every embodiment contains only a single technical solution, and such description is for clarity only, and those skilled in the art should make the description as a whole, and the technical solutions in the embodiments can also be combined appropriately to form other embodiments understood by those skilled in the art.
The above-listed detailed description is only a specific description of a possible embodiment of the present invention, and they are not intended to limit the scope of the present invention, and equivalent embodiments or modifications made without departing from the technical spirit of the present invention should be included in the scope of the present invention.

Claims (15)

1. A three-dimensional reconstruction method for blood vessels and internal plaques is characterized by comprising the following steps:
obtaining blood vessel image information of a group of blood vessel radial sections, wherein the blood vessel image information is sequentially distributed along a scanning track;
obtaining blood vessel contour information corresponding to each blood vessel image information through a blood vessel segmentation model;
screening the blood vessel contour information based on a scanning track;
obtaining plaque outline information corresponding to each blood vessel image information by passing at least part of the blood vessel image information through a plaque segmentation model;
screening the plaque outline information based on the position relation between the plaque and the blood vessel outline;
taking a group of blood vessel contour information along the scanning direction as input, and performing three-dimensional reconstruction through surface drawing to generate a blood vessel three-dimensional model;
traversing each piece of plaque contour information after screening through the blood vessel three-dimensional model to generate the blood vessel three-dimensional model with the plaque.
2. The three-dimensional reconstruction method according to claim 1, wherein the step of obtaining vessel image information of a set of vessel radial slices comprises:
acquiring a group of original images and length and depth information of the three-dimensional model which are sequentially arranged along a scanning track;
and resampling the original image to obtain blood vessel image information, wherein the blood vessel image information is a group of gray level images.
3. The three-dimensional reconstruction method according to claim 2, wherein the step of obtaining a set of original images, length and depth information of the three-dimensional model sequentially arranged along the scanning trajectory comprises:
scanning parameter information is obtained, wherein the scanning parameter information comprises scanning distance information and scanning depth information;
and calculating the length information and the depth information of the three-dimensional model according to the scanning distance information, the scanning depth information and the number information of the original images.
4. The three-dimensional reconstruction method according to claim 3, wherein the step of resampling the original image to obtain the blood vessel image information comprises:
graying and compressing the original image into a resample image, wherein the original image is a group of transverse scanning color images vertical to the extending direction of the blood vessel;
and generating a group of blood vessel image information by a linear interpolation algorithm according to the length information and the depth information by taking the resampled image as a data source.
5. The three-dimensional reconstruction method according to claim 1, wherein the step of obtaining the blood vessel contour information corresponding to each of the blood vessel image information by passing the blood vessel image information through a blood vessel segmentation model comprises:
and detecting the blood vessel image information through a blood vessel segmentation model, replacing pixels of which the gray value is greater than or equal to a preset blood vessel confidence value with a first value, and replacing pixels of which the gray value is less than the preset blood vessel confidence value with a second value to generate blood vessel contour information.
6. The three-dimensional reconstruction method according to claim 5, wherein the step of "filtering the blood vessel contour information based on a scanning trajectory" comprises:
and if the deviation value of the center point of a certain piece of blood vessel contour information and the blood vessel extension track exceeds a preset blood vessel deviation value, screening out the blood vessel contour information.
7. The three-dimensional reconstruction method according to claim 6, wherein the step of obtaining plaque contour information corresponding to each of the blood vessel image information by passing at least part of the blood vessel image information through a plaque segmentation model comprises:
and obtaining the plaque contour information corresponding to each blood vessel image information through a plaque segmentation model according to the blood vessel image information corresponding to the screened blood vessel contour information.
8. The three-dimensional reconstruction method according to claim 7, wherein the step of obtaining the plaque contour information corresponding to each of the blood vessel image information by passing the blood vessel image information corresponding to the blood vessel contour information after the screening through a plaque segmentation model includes:
detecting the blood vessel image information corresponding to the screened blood vessel contour information through a plaque segmentation model, replacing pixels of which the gray value is greater than or equal to a preset plaque confidence value with a first value, and replacing pixels of which the gray value is smaller than the preset plaque confidence value with a second value to generate plaque contour information.
9. The three-dimensional reconstruction method according to claim 8, wherein the step of "filtering the plaque contour information based on a positional relationship between plaque and a blood vessel contour" includes:
and screening the plaque outline information if the deviation degree of the area with the first value on the certain plaque outline information and the area with the first value in the corresponding blood vessel outline information is larger than a preset plaque deviation value.
10. The three-dimensional reconstruction method according to claim 9, wherein the step of performing three-dimensional reconstruction by surface rendering using a set of the blood vessel contour information along a scanning direction as an input to generate a three-dimensional model of a blood vessel comprises:
determining a first equivalence surface based on a boundary contour of a first value and a second value in the blood vessel contour information, and generating a closed gray equivalent surface through a mobile cube algorithm, wherein the gray equivalent surface is a three-dimensional model of the blood vessel;
the three-dimensional model of the blood vessel is generated as a first color.
11. The three-dimensional reconstruction method according to claim 10, wherein the step of traversing each of the screened plaque contour information through the blood vessel three-dimensional model to generate the blood vessel three-dimensional model with plaque comprises:
determining a second equipartition surface by a boundary contour of a first value and a second value in the plaque contour information in sequence along a scanning track, traversing the second equipartition surface through the blood vessel three-dimensional model, replacing the area of the second equipartition surface with a second color different from the first color, and generating the blood vessel three-dimensional model with the plaque.
12. A three-dimensional vascular and plaque-internal reconstruction device, comprising:
the acquisition module is used for acquiring a group of blood vessel image information of a blood vessel radial section, and the plurality of blood vessel image information are sequentially distributed along a scanning track;
the blood vessel contour recognition module is used for acquiring blood vessel contour information corresponding to each piece of blood vessel image information through a blood vessel segmentation model and screening the blood vessel contour information based on a scanning track;
the plaque identification module is used for acquiring plaque contour information corresponding to each blood vessel image information from at least part of the blood vessel image information through a plaque segmentation model, and screening the plaque contour information based on the position relation between plaque and blood vessel contour;
the blood vessel modeling module is used for taking a group of blood vessel contour information along the scanning direction as input, performing three-dimensional reconstruction through surface drawing and generating a blood vessel three-dimensional model;
and the plaque modeling module is used for traversing each piece of plaque contour information after screening through the blood vessel three-dimensional model to generate a blood vessel three-dimensional model with plaque.
13. A medical device, comprising: the device of claim 12 for three-dimensional reconstruction of blood vessels and internal plaques.
14. An electronic device, comprising:
a storage module storing a computer program;
a processing module, capable of implementing the steps of the blood vessel and internal plaque three-dimensional reconstruction method according to any one of claims 1 to 11 when executing the computer program.
15. A readable storage medium storing a computer program, wherein the computer program, when executed by a processing module, implements the steps of the method for three-dimensional reconstruction of blood vessels and internal plaques according to any one of claims 1 to 11.
CN202111425153.7A 2021-11-27 2021-11-27 Medical equipment, blood vessel and internal plaque three-dimensional reconstruction method and device Pending CN114170378A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111425153.7A CN114170378A (en) 2021-11-27 2021-11-27 Medical equipment, blood vessel and internal plaque three-dimensional reconstruction method and device

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111425153.7A CN114170378A (en) 2021-11-27 2021-11-27 Medical equipment, blood vessel and internal plaque three-dimensional reconstruction method and device

Publications (1)

Publication Number Publication Date
CN114170378A true CN114170378A (en) 2022-03-11

Family

ID=80481176

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111425153.7A Pending CN114170378A (en) 2021-11-27 2021-11-27 Medical equipment, blood vessel and internal plaque three-dimensional reconstruction method and device

Country Status (1)

Country Link
CN (1) CN114170378A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115147360A (en) * 2022-06-13 2022-10-04 北京医准智能科技有限公司 Plaque segmentation method and device, electronic equipment and readable storage medium
CN115661225A (en) * 2022-12-26 2023-01-31 深圳微创踪影医疗装备有限公司 Three-dimensional blood vessel image reconstruction method and device, computer equipment and storage medium

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103247071A (en) * 2013-03-29 2013-08-14 哈尔滨工业大学深圳研究生院 Method and device for constructing three-dimensional blood vessel model
CN107610107A (en) * 2017-09-01 2018-01-19 华中科技大学 A kind of three-dimensional vascular plaque features of ultrasound pattern based on dimension describes method
CN110522449A (en) * 2019-10-29 2019-12-03 南京景三医疗科技有限公司 A kind of patch classifying method, device, electronic equipment and readable storage medium storing program for executing
CN112711831A (en) * 2020-12-07 2021-04-27 上海联影医疗科技股份有限公司 Blood vessel simulation analysis method, device, apparatus, computer device and storage medium
KR20210069853A (en) * 2019-12-04 2021-06-14 충남대학교병원 Estimation of Atherosclerotic Plaque using Two Dimensional Ultrasound Images Obtained From Human Carotid Artery
CN113592879A (en) * 2021-07-29 2021-11-02 昆明同心医联科技有限公司 Carotid plaque segmentation method and device based on artificial intelligence and storage medium

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103247071A (en) * 2013-03-29 2013-08-14 哈尔滨工业大学深圳研究生院 Method and device for constructing three-dimensional blood vessel model
CN107610107A (en) * 2017-09-01 2018-01-19 华中科技大学 A kind of three-dimensional vascular plaque features of ultrasound pattern based on dimension describes method
CN110522449A (en) * 2019-10-29 2019-12-03 南京景三医疗科技有限公司 A kind of patch classifying method, device, electronic equipment and readable storage medium storing program for executing
KR20210069853A (en) * 2019-12-04 2021-06-14 충남대학교병원 Estimation of Atherosclerotic Plaque using Two Dimensional Ultrasound Images Obtained From Human Carotid Artery
CN112711831A (en) * 2020-12-07 2021-04-27 上海联影医疗科技股份有限公司 Blood vessel simulation analysis method, device, apparatus, computer device and storage medium
CN113592879A (en) * 2021-07-29 2021-11-02 昆明同心医联科技有限公司 Carotid plaque segmentation method and device based on artificial intelligence and storage medium

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
金娇英等: "两种超声颈动脉血管斑块图像分割方法比较与改进", 计算机科学, 15 June 2012 (2012-06-15) *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115147360A (en) * 2022-06-13 2022-10-04 北京医准智能科技有限公司 Plaque segmentation method and device, electronic equipment and readable storage medium
CN115147360B (en) * 2022-06-13 2023-04-04 北京医准智能科技有限公司 Plaque segmentation method and device, electronic equipment and readable storage medium
CN115661225A (en) * 2022-12-26 2023-01-31 深圳微创踪影医疗装备有限公司 Three-dimensional blood vessel image reconstruction method and device, computer equipment and storage medium
CN115661225B (en) * 2022-12-26 2023-03-21 深圳微创踪影医疗装备有限公司 Three-dimensional blood vessel image reconstruction method and device, computer equipment and storage medium

Similar Documents

Publication Publication Date Title
CN114170378A (en) Medical equipment, blood vessel and internal plaque three-dimensional reconstruction method and device
CN107292835B (en) Method and device for automatically vectorizing retinal blood vessels of fundus image
CN110705583A (en) Cell detection model training method and device, computer equipment and storage medium
CN110176010B (en) Image detection method, device, equipment and storage medium
CN113989407B (en) Training method and system for limb part recognition model in CT image
CN116503607B (en) CT image segmentation method and system based on deep learning
CN115965750B (en) Vascular reconstruction method, vascular reconstruction device, vascular reconstruction computer device, and vascular reconstruction program
CN114365190A (en) Spleen tumor identification method based on VRDS 4D medical image and related device
CN111932552B (en) Aorta modeling method and device
CN114693710A (en) Blood vessel lumen intimal contour extraction method and device, ultrasonic equipment and storage medium
CN112699885A (en) Semantic segmentation training data augmentation method and system based on antagonism generation network GAN
CN114816055A (en) Eyeball motion track capturing and analyzing method, device and medium based on VR equipment
CN113506365A (en) Image display method and related device, electronic equipment and storage medium
CN113269752A (en) Image detection method, device terminal equipment and storage medium
CN115984131A (en) Two-dimensional image edge enhancement method and application
AU2019430258B2 (en) VRDS 4D medical image-based tumor and blood vessel ai processing method and product
CN111612860B (en) VRDS 4D medical image-based Ai identification method and product for embolism
WO2021081850A1 (en) Vrds 4d medical image-based spine disease recognition method, and related devices
CN112509080A (en) Method for establishing intracranial vascular simulation three-dimensional model based on transfer learning
CN111613302B (en) Tumor Ai processing method and product based on medical image
CN111613301B (en) Arterial and venous Ai processing method and product based on VRDS 4D medical image
JP7480997B2 (en) Image processing device, image processing method, and program
CN118172352A (en) Method for constructing amniotic fluid region segmentation model, amniotic fluid index measurement method and device
CN115409690B (en) Real-time fundus image mapping method and device
CN115908825A (en) Quasi-circular structure segmentation method and device based on visual processing

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination