CN113963109A - Heart image three-dimensional reconstruction method, device, equipment and storage medium - Google Patents
Heart image three-dimensional reconstruction method, device, equipment and storage medium Download PDFInfo
- Publication number
- CN113963109A CN113963109A CN202111173409.XA CN202111173409A CN113963109A CN 113963109 A CN113963109 A CN 113963109A CN 202111173409 A CN202111173409 A CN 202111173409A CN 113963109 A CN113963109 A CN 113963109A
- Authority
- CN
- China
- Prior art keywords
- image
- heart
- cardiac
- points
- dimensional reconstruction
- 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
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/005—General purpose rendering architectures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/10—Geometric effects
- G06T15/30—Clipping
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20112—Image segmentation details
- G06T2207/20116—Active contour; Active surface; Snakes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20112—Image segmentation details
- G06T2207/20124—Active shape model [ASM]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30048—Heart; Cardiac
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Computer Graphics (AREA)
- Data Mining & Analysis (AREA)
- Geometry (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Artificial Intelligence (AREA)
- Life Sciences & Earth Sciences (AREA)
- Software Systems (AREA)
- Image Analysis (AREA)
- Image Processing (AREA)
- Apparatus For Radiation Diagnosis (AREA)
Abstract
The invention belongs to the technical field of computers, and discloses a three-dimensional reconstruction method, a three-dimensional reconstruction device, a three-dimensional reconstruction equipment and a storage medium for a heart image. The method comprises the steps of carrying out image segmentation on an input heart image to obtain three-dimensional contour points; selecting a plurality of characteristic points from the heart image, and determining the heart initial shape corresponding to the heart image according to the characteristic points; and performing three-dimensional reconstruction based on the initial shape of the heart and the three-dimensional contour points. The heart image is firstly segmented to obtain the three-dimensional contour points, then the selected feature points in the heart image are transformed to obtain the heart initial shape, and finally the heart initial shape and the three-dimensional contour points are combined to carry out three-dimensional modeling together, so that the accuracy of the three-dimensional modeling can be improved.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method, a device, equipment and a storage medium for three-dimensional reconstruction of a heart image.
Background
Clinically, assessment of cardiac ejection fraction and myocardial mass, as well as other functional parameters (such as wall motion and wall thickness) is one of the important tools for early diagnosis of heart disease. However, the heart is a three-dimensional organ with a complex structure and having contraction and relaxation motions, and the clinical effect of heart motion parameters in describing local abnormalities and early-stage micro lesions is obvious, which requires accurate segmentation of the three-dimensional structure for heart images of different phases (different moments in the relaxation phase and the contraction phase), and three-dimensional modeling is performed according to the segmentation result to obtain accurate static and dynamic parameters of the heart. However, as the temporal and spatial resolution of the imaging device is greatly improved, the segmentation difficulty is greatly increased by the massive amount of image data.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide a method, a device, equipment and a storage medium for three-dimensional reconstruction of a heart image, and aims to solve the technical problems that in the prior art, the heart image is difficult to be accurately segmented, and three-dimensional modeling is difficult.
In order to achieve the above object, the present invention provides a three-dimensional reconstruction method for cardiac images, comprising the steps of:
carrying out image segmentation on an input heart image to obtain three-dimensional contour points;
selecting a plurality of characteristic points in the heart image, and determining the initial shape of the heart corresponding to the heart image according to the characteristic points;
and performing three-dimensional reconstruction based on the initial shape of the heart and the three-dimensional contour points.
Optionally, the step of selecting a plurality of feature points from the cardiac image and determining an initial shape of a heart corresponding to the cardiac image according to the feature points includes:
selecting outflow tract characteristic points, intermediate layer characteristic points and apical characteristic points from the heart image;
and determining the initial shape of the heart corresponding to the heart image through a preset point distribution model based on the outflow tract feature points, the intermediate layer feature points and the apex feature points.
Optionally, the step of selecting outflow tract feature points, intermediate layer feature points, and apical feature points in the cardiac image includes:
acquiring a first outflow channel mark image, a second outflow channel mark image, an intermediate layer mark image and an apex mark image;
selecting an outflow tract feature point in the heart image according to the first outflow tract marker image and the second outflow tract marker image;
selecting intermediate layer feature points in the heart image according to the intermediate layer marker image;
and selecting an apex feature point in the heart image according to the apex marker image.
Optionally, the step of selecting an outflow tract feature point in the cardiac image according to the first outflow tract marker image and the second outflow tract marker image includes:
respectively carrying out image registration on the first outflow tract marker image and the second outflow tract marker image and the heart image to obtain a first registration image and a second registration image;
performing similarity matching on the first registration image and the heart image to obtain a first similarity;
performing similarity matching on the second registration image and the heart image to obtain a second similarity;
and comparing the first similarity with the second similarity, and selecting outflow tract feature points in the heart image according to the comparison result.
Optionally, the step of comparing the first similarity with the second similarity and selecting an outflow tract feature point in the cardiac image according to a comparison result includes:
comparing the first similarity with the second similarity;
if the first similarity is larger than the second similarity, selecting an outflow tract feature point in the heart image according to the first outflow tract marker image;
and if the second similarity is greater than the first similarity, selecting an outflow tract feature point in the heart image according to the second outflow tract marker image.
Optionally, the step of performing three-dimensional reconstruction based on the initial shape of the heart and the three-dimensional contour points includes:
establishing a coordinate system based on the cardiac image;
determining outline points of the heart bottom layer according to the three-dimensional outline points, and adjusting the heart image to enable a plane formed by the outline points of the heart bottom layer to be positioned in the horizontal direction;
adjusting the heart initial shape to enable a heart bottom layer in the heart initial shape to be located in the horizontal direction;
and mapping the initial heart shape to a coordinate system in the heart image to obtain a three-dimensional reconstruction image.
Optionally, the step of mapping the initial shape of the heart into a coordinate system in the heart image to obtain a three-dimensional reconstructed image includes:
determining a cardiac fundus layer and a cardiac apical layer in the cardiac image based on the three-dimensional contour points;
vertically stretching the left ventricle and the right ventricle in the heart initial shape to enable the heart bottom layer and the heart apex layer in the heart initial shape to cover the heart bottom layer and the heart apex layer in the heart image, and obtaining the stretched heart initial shape;
and mapping the stretched initial shape of the heart to a coordinate system in the heart image to obtain a three-dimensional reconstruction image.
In addition, to achieve the above object, the present invention further provides a three-dimensional reconstruction apparatus for cardiac images, including the following modules:
the image segmentation module is used for carrying out image segmentation on the input heart image to obtain three-dimensional contour points;
the shape determining module is used for selecting a plurality of characteristic points in the heart image and determining the initial shape of the heart corresponding to the heart image according to the characteristic points;
and the three-dimensional reconstruction module is used for performing three-dimensional reconstruction based on the initial shape of the heart and the three-dimensional contour points.
Furthermore, to achieve the above object, the present invention also provides a three-dimensional reconstruction apparatus for cardiac images, comprising: a processor, a memory and a three-dimensional reconstruction program of cardiac images stored on the memory and executable on the processor, the three-dimensional reconstruction program of cardiac images implementing the steps of the three-dimensional reconstruction method of cardiac images as described above when executed by the processor.
In addition, to achieve the above object, the present invention further provides a computer readable storage medium, which stores thereon a three-dimensional reconstruction program of a cardiac image, the three-dimensional reconstruction program implementing the steps of the three-dimensional reconstruction method of a cardiac image as described above when executed.
The method comprises the steps of carrying out image segmentation on an input heart image to obtain three-dimensional contour points; selecting a plurality of characteristic points from the heart image, and determining the heart initial shape corresponding to the heart image according to the characteristic points; and performing three-dimensional reconstruction based on the initial shape of the heart and the three-dimensional contour points. The heart image is firstly segmented to obtain the three-dimensional contour points, then the selected feature points in the heart image are transformed to obtain the heart initial shape, and finally the heart initial shape and the three-dimensional contour points are combined to carry out three-dimensional modeling together, so that the accuracy of the three-dimensional modeling can be improved.
Drawings
Fig. 1 is a schematic structural diagram of an electronic device in a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flowchart of a first embodiment of a method for three-dimensional reconstruction of cardiac images according to the present invention;
FIG. 3 is a flowchart illustrating a three-dimensional reconstruction method of a cardiac image according to a second embodiment of the present invention;
fig. 4 is a block diagram of a three-dimensional reconstruction apparatus for cardiac images according to a first embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a cardiac image three-dimensional reconstruction apparatus in a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the electronic device may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wireless-Fidelity (WI-FI) interface). The Memory 1005 may be a Random Access Memory (RAM) or a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration shown in fig. 1 does not constitute a limitation of the electronic device and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a storage medium, may include therein an operating system, a network communication module, a user interface module, and a cardiac image three-dimensional reconstruction program.
In the electronic apparatus shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 of the electronic device of the present invention may be provided in a cardiac image three-dimensional reconstruction device, and the electronic device calls the cardiac image three-dimensional reconstruction program stored in the memory 1005 through the processor 1001 and executes the cardiac image three-dimensional reconstruction method provided by the embodiment of the present invention.
An embodiment of the present invention provides a three-dimensional cardiac image reconstruction method, and referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of a three-dimensional cardiac image reconstruction method according to the present invention.
In this embodiment, the three-dimensional reconstruction method for cardiac images includes the following steps:
step S10: and carrying out image segmentation on the input heart image to obtain three-dimensional contour points.
It should be noted that, the execution subject of this embodiment may be the cardiac image three-dimensional reconstruction device, and the cardiac image three-dimensional reconstruction device may be an electronic device such as a personal computer, a server, or the like, or may be a device that can implement the same or similar functions.
It should be noted that the cardiac image may be a short-axis cardiac image, and the cardiac image may be manually input by a user or may be acquired and input by an image acquisition device, which is not limited in this embodiment, where the image acquisition device may be a magnetic resonance imaging device. The input cardiac images may be multiple and may include cardiac images at different phases. The image segmentation of the input heart image to obtain the three-dimensional contour points may be performed by performing image segmentation on the input heart image through a preset image segmentation model, determining to divide each region of the heart in the heart image, and extracting the contour points of each region of the heart to obtain the three-dimensional contour points, for example: the method comprises the steps of segmenting an input heart image through a preset image segmentation model, dividing left and right ventricle areas of a heart, and extracting three-dimensional contour points based on the left and right ventricle areas of the heart. The preset image segmentation model may be a neural network model trained in advance using a large number of samples for image segmentation.
Step S20: selecting a plurality of characteristic points in the heart image, and determining the initial shape of the heart corresponding to the heart image according to the characteristic points.
The feature points may be feature points of different regions of the heart, and after the feature points of the heart image in different time phases are acquired, an average shape of the heart may be acquired, and the average shape may be subjected to complex transformation such as stretching and rotation based on the acquired feature points of the heart, so that an initial shape of the heart may be acquired.
Further, in order to improve the efficiency of determining the initial shape of the heart, step S20 of this embodiment may include:
selecting outflow tract characteristic points, intermediate layer characteristic points and apical characteristic points from the heart image;
and determining the initial shape of the heart corresponding to the heart image through a preset point distribution model based on the outflow tract feature points, the intermediate layer feature points and the apex feature points.
It should be noted that the preset point distribution model may be a pre-trained neural network model or a deep learning model. The outflow tract characteristic points can be characteristic points selected in the outflow tract area of the left ventricle of the heart, the intermediate layer characteristic points can be characteristic points selected in the intermediate layer of the right ventricle of the heart, and the apical characteristic points can be characteristic points selected in the apical areas of the left ventricle and the right ventricle of the heart.
In practical use, the preset point distribution model is preset with a plurality of feature points, and only the positions of the feature points in the heart image need to be determined, the preset point distribution model can perform composite transformation on the average shape of the heart according to the marked feature point positions, so that the initial shape of the heart can be obtained, wherein the average shape of the heart can be generated when the point distribution model is trained by adopting a large number of samples.
For example: the preset point distribution model sets five characteristic points including an AORTA (AORTA), a MITRAL valve (MITRAL), a Left Ventricle Apex (LVAPEX), a Tricuspid (TRICUPSID) and a Right Ventricle Apex (RVAPEX). Then the outflow tract feature points may include aortic (AORTA), MITRAL (miral) feature points, the intermediate layer feature points may include tricuspid (tricuspid) feature points, and the apex feature points may include Left Ventricular Apex (LVAPEX), Right Ventricular Apex (RVAPEX) feature points.
Further, due to the difference of imaging environments, there may be a situation that a left ventricular outflow tract image is missing in a short-axis sequence image of a heart, and in order to ensure that each feature point can be accurately selected, the step of selecting an outflow tract feature point, an intermediate layer feature point, and an apical feature point in the cardiac image in this embodiment may include:
acquiring a first outflow channel mark image, a second outflow channel mark image, an intermediate layer mark image and an apex mark image;
selecting an outflow tract feature point in the heart image according to the first outflow tract marker image and the second outflow tract marker image;
selecting intermediate layer feature points in the heart image according to the intermediate layer marker image;
and selecting an apex feature point in the heart image according to the apex marker image.
It should be noted that the first outflow tract marker image may be a short-axis cardiac fundus image containing the left ventricular outflow tract in which the expert-marked outflow tract feature points are present. The second outflow tract marker image may be a short axis cardiac fundus image without the left ventricular outflow tract in which the expert marked outflow tract feature points are present. The intermediate layer marker image may be a short axis cardiac intermediate layer image in which the expert marked intermediate layer feature points are present. The apex marker image may be a short axis cardiac fundus image in which the expert marked apex layer feature points are present.
In practical use, the step of selecting the outflow tract feature point in the cardiac image according to the first outflow tract marker image and the second outflow tract marker image may be to compare the similarity of the cardiac image with the first outflow tract marker image and the second outflow tract marker image, select a target marker image with a higher similarity from the first outflow tract marker image and the second outflow tract marker image according to a comparison result, and select the outflow tract feature point in the cardiac image according to the target marker image. The feature points marked in the marked image by the expert in the cardiac image can be selected according to the marked image by adopting a label transfer mode to convert the feature points marked in the marked image by the expert in the cardiac image into the feature points in the cardiac image, wherein the marked image can be any one of a first outflow tract marked image, a second outflow tract marked image, an intermediate layer marked image and an apex marked image.
Further, in order to ensure that the selected outflow tract feature points are as accurate as possible, in this embodiment, the step of selecting the outflow tract feature points in the cardiac image according to the first outflow tract marker image and the second outflow tract marker image may include:
respectively carrying out image registration on the first outflow tract marker image and the second outflow tract marker image and the heart image to obtain a first registration image and a second registration image;
performing similarity matching on the first registration image and the heart image to obtain a first similarity;
performing similarity matching on the second registration image and the heart image to obtain a second similarity;
and comparing the first similarity with the second similarity, and selecting outflow tract feature points in the heart image according to the comparison result.
It should be noted that, the first outflow tract marker image and the second outflow tract marker image are respectively subjected to image registration with the cardiac image, and the first registration image and the second registration image are obtained by performing image registration on the first outflow tract marker image and the cardiac image through a preset image registration algorithm to obtain a first registration image, and performing image registration on the second outflow tract marker image and the cardiac image through a preset image registration algorithm to obtain a second registration image, where the preset image registration algorithm may be a rigid registration algorithm or a non-rigid registration algorithm, and this embodiment does not limit this.
The similarity matching is performed between the first registration image and the cardiac image, and the obtaining of the first similarity may be performed by performing similarity matching between the first registration image and the cardiac image through a preset similarity index, so as to obtain the first similarity. And performing similarity matching on the second registration image and the cardiac image, wherein the obtaining of the second similarity may be performing similarity matching on the second registration image and the cardiac image through a preset similarity index to obtain the second similarity. The preset similarity measure may be an index such as maximum mutual information or am (alignment metric) measure.
In practical use, the comparing the first similarity with the second similarity, and selecting the outflow tract feature point in the cardiac image according to the comparison result may be comparing the first similarity with the second similarity, generating the comparison result, selecting the target mark image in the first outflow tract mark image and the second outflow tract mark image according to the comparison result, and then selecting the outflow tract feature point in the cardiac image according to the target mark image.
It can be understood that, if the comparison result shows that the first similarity is greater than the second similarity, it indicates that the similarity between the first registered image and the cardiac image is higher than the similarity between the second registered image and the cardiac image, and it indicates that the left ventricular outflow tract image exists in the cardiac image, and therefore, the first outflow tract marker image may be used as a target marker image, and an outflow tract feature point may be selected in the cardiac image according to the first outflow tract marker image. On the contrary, if the comparison result is that the second similarity is greater than the first similarity, it indicates that the cardiac image does not include the left ventricular outflow tract image, and therefore, the second outflow tract marker image may be used as the target marker image, and the outflow tract feature point may be selected in the cardiac image according to the second outflow tract marker image.
Step S30: and performing three-dimensional reconstruction based on the initial shape of the heart and the three-dimensional contour points.
It can be understood that after the three-dimensional contour points of each region of the heart in the heart image are determined by image segmentation, the three-dimensional reconstruction can be completed by mapping the obtained heart initial shape to the three-dimensional contour points for mapping, and the three-dimensional modeling result of the heart is obtained.
It can be understood that the heart is a moving organ, and the three-dimensional modeling result obtained by segmenting the heart image of the first time phase is only required to be given to the initial shape of the second time phase, and so on, so that the three-dimensional modeling result of the heart under all the time phases can be obtained.
The embodiment obtains three-dimensional contour points by performing image segmentation on an input heart image; selecting a plurality of characteristic points from the heart image, and determining the heart initial shape corresponding to the heart image according to the characteristic points; and performing three-dimensional reconstruction based on the initial shape of the heart and the three-dimensional contour points. The heart image is firstly segmented to obtain the three-dimensional contour points, then the selected feature points in the heart image are transformed to obtain the heart initial shape, and finally the heart initial shape and the three-dimensional contour points are combined to carry out three-dimensional modeling together, so that the accuracy of the three-dimensional modeling can be improved.
Referring to fig. 3, fig. 3 is a flowchart illustrating a three-dimensional reconstruction method of a cardiac image according to a second embodiment of the present invention.
Based on the first embodiment, the step S30 of the method for three-dimensional reconstruction of cardiac images in this embodiment includes:
step S301: a coordinate system is established based on the cardiac image.
It should be noted that the establishment of the coordinate system based on the cardiac image may be establishment of the coordinate system by selecting an arbitrary point in the cardiac image as an origin.
Step S302: and determining outline points of the heart bottom layer according to the three-dimensional outline points, and adjusting the heart image to enable the plane formed by the outline points of the heart bottom layer to be positioned in the horizontal direction.
It should be noted that, determining the outline points of the heart bottom layer according to the three-dimensional outline points, adjusting the heart image to make the plane formed by the outline points of the heart bottom layer be located in the horizontal direction, or screening the outline points of the heart bottom layer from the three-dimensional outline points, determining the plane formed by the outline points of the heart bottom layer, and rotating the heart image to make the outline points of the heart bottom layer be contracted into the plane which is located in the horizontal reverse direction in the constructed coordinate system.
Step S303: and adjusting the initial heart shape to enable the bottom layer in the initial heart shape to be positioned in the horizontal direction.
It is understood that the initial shape of the heart may be adjusted by rotating the initial shape of the heart so that the bottom layer of the initial shape of the heart is located in the horizontal direction.
Step S304: and mapping the initial heart shape to a coordinate system in the heart image to obtain a three-dimensional reconstruction image.
The three-dimensional reconstructed image may be obtained by mapping the heart initial shape into a coordinate system of the heart image, that is, mapping the heart initial shape into the heart region in the heart image in a one-to-one correspondence manner, performing inverse transformation on the heart initial shape, transforming the heart initial shape into the coordinate system in the heart image, and then segmenting the heart initial shape according to the three-dimensional contour points.
Further, since in an actual process, the constructed heart initial shape is often difficult to be effectively covered on the fundus layer and the apical layer in the heart image, in order to ensure the effect of three-dimensional reconstruction, the step S304 of this embodiment may include:
determining a cardiac fundus layer and a cardiac apical layer in the cardiac image based on the three-dimensional contour points;
vertically stretching the left ventricle and the right ventricle in the heart initial shape to enable the heart bottom layer and the heart apex layer in the heart initial shape to cover the heart bottom layer and the heart apex layer in the heart image, and obtaining the stretched heart initial shape;
and mapping the stretched initial shape of the heart to a coordinate system in the heart image to obtain a three-dimensional reconstruction image.
It can be understood that the left ventricle and the right ventricle in the heart initial shape are vertically stretched, and the heart bottom layer and the heart apex layer in the heart initial shape are covered on the heart bottom layer and the heart apex layer in the heart image, so that the stretched heart initial shape can effectively cover the heart in the heart image, and the heart initial shape can be accurately segmented according to the three-dimensional contour points, and an accurate three-dimensional reconstruction image is obtained.
This embodiment is achieved by establishing a coordinate system based on the cardiac image; determining outline points of the heart bottom layer according to the three-dimensional outline points, and adjusting the heart image to enable a plane formed by the outline points of the heart bottom layer to be positioned in the horizontal direction; adjusting the heart initial shape to enable a heart bottom layer in the heart initial shape to be located in the horizontal direction; and mapping the initial heart shape to a coordinate system in the heart image to obtain a three-dimensional reconstruction image. Before three-dimensional modeling is carried out according to the three-dimensional contour points and the heart initial shape, the heart bottom layer of the heart is used as a reference, the heart image and the heart initial shape are adjusted, and three-dimensional modeling is carried out after the heart bottom layer and the heart initial shape in the heart image are located on the same horizontal plane, so that the accuracy of three-dimensional modeling is further improved.
Furthermore, an embodiment of the present invention further provides a storage medium, on which a cardiac image three-dimensional reconstruction program is stored, which when executed by a processor implements the steps of the cardiac image three-dimensional reconstruction method as described above.
Referring to fig. 4, fig. 4 is a block diagram illustrating a three-dimensional reconstruction apparatus of a cardiac image according to a first embodiment of the present invention.
As shown in fig. 4, a three-dimensional reconstruction apparatus for cardiac images according to an embodiment of the present invention includes:
an image segmentation module 10, configured to perform image segmentation on an input cardiac image to obtain three-dimensional contour points;
a shape determining module 20, configured to select a plurality of feature points in the cardiac image, and determine an initial shape of a heart corresponding to the cardiac image according to the feature points;
and a three-dimensional reconstruction module 30, configured to perform three-dimensional reconstruction based on the initial shape of the heart and the three-dimensional contour points.
The embodiment obtains three-dimensional contour points by performing image segmentation on an input heart image; selecting a plurality of characteristic points from the heart image, and determining the heart initial shape corresponding to the heart image according to the characteristic points; and performing three-dimensional reconstruction based on the initial shape of the heart and the three-dimensional contour points. The heart image is firstly segmented to obtain the three-dimensional contour points, then the selected feature points in the heart image are transformed to obtain the heart initial shape, and finally the heart initial shape and the three-dimensional contour points are combined to carry out three-dimensional modeling together, so that the accuracy of the three-dimensional modeling can be improved.
Further, the shape determining module 20 is further configured to select outflow tract feature points, intermediate layer feature points, and apical feature points in the cardiac image; and determining the initial shape of the heart corresponding to the heart image through a preset point distribution model based on the outflow tract feature points, the intermediate layer feature points and the apex feature points.
Further, the shape determining module 20 is further configured to obtain a first outflow tract marker image, a second outflow tract marker image, an intermediate layer marker image, and an apex marker image; selecting an outflow tract feature point in the heart image according to the first outflow tract marker image and the second outflow tract marker image; selecting intermediate layer feature points in the heart image according to the intermediate layer marker image; and selecting an apex feature point in the heart image according to the apex marker image.
Further, the shape determining module 20 is further configured to perform image registration on the first outflow tract marker image and the second outflow tract marker image with the cardiac image, respectively, to obtain a first registration image and a second registration image; performing similarity matching on the first registration image and the heart image to obtain a first similarity; performing similarity matching on the second registration image and the heart image to obtain a second similarity; and comparing the first similarity with the second similarity, and selecting outflow tract feature points in the heart image according to the comparison result.
Further, the shape determining module 20 is further configured to compare the first similarity with the second similarity; if the first similarity is larger than the second similarity, selecting an outflow tract feature point in the heart image according to the first outflow tract marker image; and if the second similarity is greater than the first similarity, selecting an outflow tract feature point in the heart image according to the second outflow tract marker image.
Further, the three-dimensional reconstruction module 30 is further configured to establish a coordinate system based on the cardiac image; determining outline points of the heart bottom layer according to the three-dimensional outline points, and adjusting the heart image to enable a plane formed by the outline points of the heart bottom layer to be positioned in the horizontal direction; adjusting the heart initial shape to enable a heart bottom layer in the heart initial shape to be located in the horizontal direction; and mapping the initial heart shape to a coordinate system in the heart image to obtain a three-dimensional reconstruction image.
Further, the three-dimensional reconstruction module 30 is further configured to determine a cardiac fundus layer and a cardiac apical layer in the cardiac image based on the three-dimensional contour points; vertically stretching the left ventricle and the right ventricle in the heart initial shape to enable the heart bottom layer and the heart apex layer in the heart initial shape to cover the heart bottom layer and the heart apex layer in the heart image, and obtaining the stretched heart initial shape; and mapping the stretched initial shape of the heart to a coordinate system in the heart image to obtain a three-dimensional reconstruction image.
It should be understood that the above is only an example, and the technical solution of the present invention is not limited in any way, and in a specific application, a person skilled in the art may set the technical solution as needed, and the present invention is not limited thereto.
It should be noted that the above-described work flows are only exemplary, and do not limit the scope of the present invention, and in practical applications, a person skilled in the art may select some or all of them to achieve the purpose of the solution of the embodiment according to actual needs, and the present invention is not limited herein.
In addition, the technical details that are not elaborated in this embodiment may be referred to a three-dimensional reconstruction method of a cardiac image provided in any embodiment of the present invention, and are not described herein again.
Further, it is to be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention or portions thereof that contribute to the prior art may be embodied in the form of a software product, where the computer software product is stored in a storage medium (e.g. Read Only Memory (ROM)/RAM, magnetic disk, optical disk), and includes several instructions for enabling a terminal device (e.g. a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A three-dimensional reconstruction method for cardiac images is characterized by comprising the following steps:
carrying out image segmentation on an input heart image to obtain three-dimensional contour points;
selecting a plurality of characteristic points in the heart image, and determining the initial shape of the heart corresponding to the heart image according to the characteristic points;
and performing three-dimensional reconstruction based on the initial shape of the heart and the three-dimensional contour points.
2. The method for three-dimensional reconstruction of cardiac image according to claim 1, wherein the step of selecting a plurality of feature points in the cardiac image and determining the initial shape of the heart corresponding to the cardiac image according to the feature points comprises:
selecting outflow tract characteristic points, intermediate layer characteristic points and apical characteristic points from the heart image;
and determining the initial shape of the heart corresponding to the heart image through a preset point distribution model based on the outflow tract feature points, the intermediate layer feature points and the apex feature points.
3. The method for three-dimensional reconstruction of cardiac image according to claim 2, wherein the step of selecting the outflow tract feature points, the intermediate layer feature points and the apex feature points in the cardiac image comprises:
acquiring a first outflow channel mark image, a second outflow channel mark image, an intermediate layer mark image and an apex mark image;
selecting an outflow tract feature point in the heart image according to the first outflow tract marker image and the second outflow tract marker image;
selecting intermediate layer feature points in the heart image according to the intermediate layer marker image;
and selecting an apex feature point in the heart image according to the apex marker image.
4. The method for three-dimensional reconstruction of cardiac image according to claim 3, wherein the step of selecting the outflow tract feature points in the cardiac image according to the first outflow tract marker image and the second outflow tract marker image comprises:
respectively carrying out image registration on the first outflow tract marker image and the second outflow tract marker image and the heart image to obtain a first registration image and a second registration image;
performing similarity matching on the first registration image and the heart image to obtain a first similarity;
performing similarity matching on the second registration image and the heart image to obtain a second similarity;
and comparing the first similarity with the second similarity, and selecting outflow tract feature points in the heart image according to the comparison result.
5. The method for three-dimensional reconstruction of cardiac image according to claim 4, wherein the step of comparing the first similarity with the second similarity and selecting the outflow tract feature points in the cardiac image according to the comparison result comprises:
comparing the first similarity with the second similarity;
if the first similarity is larger than the second similarity, selecting an outflow tract feature point in the heart image according to the first outflow tract marker image;
and if the second similarity is greater than the first similarity, selecting an outflow tract feature point in the heart image according to the second outflow tract marker image.
6. The method for three-dimensional reconstruction of cardiac images according to claim 1, wherein the step of three-dimensional reconstruction based on the initial shape of the heart and the three-dimensional contour points comprises:
establishing a coordinate system based on the cardiac image;
determining outline points of the heart bottom layer according to the three-dimensional outline points, and adjusting the heart image to enable a plane formed by the outline points of the heart bottom layer to be positioned in the horizontal direction;
adjusting the heart initial shape to enable a heart bottom layer in the heart initial shape to be located in the horizontal direction;
and mapping the initial heart shape to a coordinate system in the heart image to obtain a three-dimensional reconstruction image.
7. The method for three-dimensional reconstruction of cardiac images according to claim 6, wherein said step of mapping said initial shape of the heart into a coordinate system in said cardiac images to obtain three-dimensional reconstructed images comprises:
determining a cardiac fundus layer and a cardiac apical layer in the cardiac image based on the three-dimensional contour points;
vertically stretching the left ventricle and the right ventricle in the heart initial shape to enable the heart bottom layer and the heart apex layer in the heart initial shape to cover the heart bottom layer and the heart apex layer in the heart image, and obtaining the stretched heart initial shape;
and mapping the stretched initial shape of the heart to a coordinate system in the heart image to obtain a three-dimensional reconstruction image.
8. A three-dimensional reconstruction device for cardiac images is characterized by comprising the following modules:
the image segmentation module is used for carrying out image segmentation on the input heart image to obtain three-dimensional contour points;
the shape determining module is used for selecting a plurality of characteristic points in the heart image and determining the initial shape of the heart corresponding to the heart image according to the characteristic points;
and the three-dimensional reconstruction module is used for performing three-dimensional reconstruction based on the initial shape of the heart and the three-dimensional contour points.
9. A three-dimensional reconstruction apparatus for cardiac images, characterized in that it comprises: a processor, a memory and a three-dimensional reconstruction program of cardiac images stored on the memory and executable on the processor, which when executed by the processor implements the steps of the method of three-dimensional reconstruction of cardiac images as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, on which a cardiac image three-dimensional reconstruction program is stored, which when executed performs the steps of the cardiac image three-dimensional reconstruction method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111173409.XA CN113963109A (en) | 2021-10-08 | 2021-10-08 | Heart image three-dimensional reconstruction method, device, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111173409.XA CN113963109A (en) | 2021-10-08 | 2021-10-08 | Heart image three-dimensional reconstruction method, device, equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113963109A true CN113963109A (en) | 2022-01-21 |
Family
ID=79463611
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111173409.XA Pending CN113963109A (en) | 2021-10-08 | 2021-10-08 | Heart image three-dimensional reconstruction method, device, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113963109A (en) |
-
2021
- 2021-10-08 CN CN202111173409.XA patent/CN113963109A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zhuang | Multivariate mixture model for myocardial segmentation combining multi-source images | |
| Mitchell et al. | 3-D active appearance models: segmentation of cardiac MR and ultrasound images | |
| Gupta et al. | Texas 3D face recognition database | |
| CN105074775B (en) | The registration of medical image | |
| JP5438029B2 (en) | Automatic 3D segmentation of short axis delay-enhanced cardiac MRI | |
| US8861891B2 (en) | Hierarchical atlas-based segmentation | |
| DE102007046582A1 (en) | System and method for segmenting chambers of a heart in a three-dimensional image | |
| KR19980041862A (en) | Myocardial Measurement System in Cardiac Imaging | |
| CN107909622A (en) | Model generating method, the scanning planing method of medical imaging and medical image system | |
| CN111488872B (en) | Image detection method, image detection device, computer equipment and storage medium | |
| CN111311737B (en) | Three-dimensional modeling method, device and equipment for heart image and storage medium | |
| US11334995B2 (en) | Hierarchical systems and methods for image segmentation | |
| JP2019028887A (en) | Image processing method | |
| Cai et al. | Accurate weakly supervised deep lesion segmentation on CT scans: Self-paced 3D mask generation from RECIST | |
| CN101504727A (en) | Image processing apparatus and method thereof | |
| CN112950684B (en) | Target feature extraction method, device, equipment and medium based on surface registration | |
| CN113129418B (en) | Target surface reconstruction method, device, equipment and medium based on three-dimensional image | |
| JP4887491B2 (en) | MEDICAL IMAGE PROCESSING METHOD, DEVICE THEREOF, AND PROGRAM | |
| CN111724395A (en) | Heart image four-dimensional context segmentation method, device, storage medium and device | |
| JP2022111705A (en) | Leaning device, image processing apparatus, medical image pick-up device, leaning method, and program | |
| JP2022111704A (en) | Image processing apparatus, medical image pick-up device, image processing method, and program | |
| CN113222996A (en) | Heart segmentation quality evaluation method, device, equipment and storage medium | |
| Piazzese et al. | Segmentation of the left ventricular endocardium from magnetic resonance images by using different statistical shape models | |
| CN113963109A (en) | Heart image three-dimensional reconstruction method, device, equipment and storage medium | |
| CN112767530B (en) | Heart image three-dimensional reconstruction method, device, equipment and storage medium |
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 |