CN111047679A - Aorta three-dimensional reconstruction visualization system based on B-S framework - Google Patents
Aorta three-dimensional reconstruction visualization system based on B-S framework Download PDFInfo
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Abstract
The invention provides an aorta three-dimensional reconstruction visualization system based on a B-S framework, which comprises: the acquisition module is arranged at the browser end and used for receiving an aorta image three-dimensional reconstruction request and acquiring an original aorta CT sequence to be processed; the first sending module is arranged at the browser end and used for sending the request to the background server end in an instruction form; the transmission module is arranged at the background server end and used for receiving the instruction and transmitting the instruction as the input parameter to the algorithm engine end; the image reconstruction module is arranged at the algorithm engine end and used for performing aorta image three-dimensional reconstruction processing according to the entry parameter so as to obtain a reconstructed aorta 3D model; the second sending module is arranged at the algorithm engine end and used for sending the reconstructed aorta 3D model to the browser end; and the presentation module is arranged at the browser end and used for receiving and presenting the reconstructed aorta 3D model. From the above, the present application can visualize the rendering of the aorta image by three-dimensional reconstruction.
Description
Technical Field
The invention relates to the field of medical images, the field of IT internet and the field of computer graphics, in particular to an aorta three-dimensional reconstruction visualization system based on a B-S framework.
Background
The aortic dissection lesion is caused by aortic intimal tear, and blood flows from a laceration to a false cavity formed between the aortic intimal and a blood vessel wall to be separated from an original true cavity. For type B aortic dissection, the first breach is located below the aortic arch. While not lethal enough in the early stages of dissection, once the dissection is broken, the blood flow breaks through the adventitia and the probability of sudden death of the patient is extremely high. Therefore, early diagnosis, early detection, and early treatment are required for these diseases.
Many researchers have studied the mathematical principle and application scenario of the image segmentation technology so far. Conventional image segmentation methods can be roughly classified into region-based segmentation algorithms, threshold-based segmentation algorithms, edge-information-based segmentation algorithms, and a mixture of the above algorithms. In a segmentation algorithm developed in recent years based on a deep learning theory, a prediction model is generated by training a large amount of manually labeled data, so that the purpose of predicting a region of interest is achieved, and a segmentation process is finally realized.
Based on the method, the whole blood vessel, the real cavity and the false cavity are separated from the aorta CTA scanning sequence by utilizing a three-dimensional image segmentation technology, so that a doctor can obtain operation scheme parameters to select a covered stent with a suitable specification for treatment. However, for aortic CTA three-dimensional data, the 3D visualization of the segmentation results for three-dimensional reconstruction of the original data will make the results more intuitive to present. The three-dimensional reconstruction and post-processing technology is provided by workstation software and single machine software of a dicom viewer of some equipment manufacturers at present, however, the three-dimensional reconstruction technology based on the B/S internet architecture is different from the traditional software in the technical theory, and at the same time, the realized software on the market is few at present; from another perspective, the three-dimensional reconstruction technology is combined with the aorta segmentation visualization result, and the system is embodied by a B/S internet technology architecture, which is rarely mentioned and realized at present.
Therefore, there is a need for a B-S architecture based aorta three-dimensional reconstruction visualization system to visualize the aorta image through three-dimensional reconstruction.
Disclosure of Invention
In view of the above, the present application provides a B-S architecture based aorta three-dimensional reconstruction visualization system for rendering an aorta image through three-dimensional reconstruction visualization.
Specifically, the application provides a visualization system for three-dimensional reconstruction of aorta based on B-S architecture, comprising:
the acquisition module is arranged at the browser end and used for receiving an aorta image three-dimensional reconstruction request and acquiring an original aorta CT sequence to be processed;
the first sending module is arranged at the browser end and used for sending the request to the background server end in an instruction form;
the transmission module is arranged at the background server end and used for receiving the instruction and transmitting the instruction as an input parameter to the algorithm engine end;
the image reconstruction module is arranged at the algorithm engine end and used for performing 3D model reconstruction processing on the aorta according to the entry parameter;
the second sending module is arranged at the algorithm engine end and used for sending the reconstructed aorta 3D model to the browser end;
and the presentation module is arranged at the browser end and used for receiving and presenting the 3D aorta model after the reconstruction processing.
From the above, the present application realizes the visualization of the aorta image through the three-dimensional reconstruction by the above system.
Preferably, the image reconstruction module includes:
the reading and constructing submodule is used for reading the original CT sequence of the aorta and constructing three-dimensional volume data;
and the rendering submodule is used for performing three-dimensional rendering processing on the three-dimensional volume data according to the parameter input requirement.
Preferably, the system further comprises:
and the storage module is used for storing the reconstructed aorta 3D model to a specified memory area.
Preferably, the system further comprises:
the viewing module is arranged at the browser end and used for receiving different viewing requests and sending the requests to the background server end;
and the third sending module is arranged at the background server end and used for calling the corresponding aorta 3D model stored in the specified memory area according to the instruction and sending the aorta 3D model to the rendering module at the browser end.
From the above, the viewing request may be a viewing request for movement, rotation, zoom, and color, transparency adjustment, etc. of the corresponding 3D model of the aorta generated by operations of mouse movement, slide up and down, etc.
Preferably, the three-dimensional rendering process of the rendering sub-module includes:
and combining the surface rendering result of the region of interest and the volume rendering result of the original region by adopting a rendering mode of combining surface rendering and volume rendering to obtain a three-dimensional image model after three-dimensional rendering processing.
Therefore, the surface drawing result of the region of interest is combined with the volume drawing result of the original region, so that original information can be retained to the maximum extent, the region of interest is highlighted, and the memory overhead burden of the server can be increased to the minimum extent.
Preferably, the image reconstruction module further includes:
the center line extraction submodule is used for extracting the center line of the blood vessel cavity;
the fusion sub-module is used for fusing and displaying the blood vessel cavity central line and the three-dimensional image model;
the standard vertical plane generation submodule is used for generating a blood vessel standard vertical plane;
and the positioning sub-module is used for providing space positioning of the standard vertical plane.
Therefore, the extracted blood vessel cavity center line and the three-dimensional image model are subjected to fusion display, a space positioning function of a standard vertical plane is provided, and a doctor can browse the standard vertical plane of the aorta and quickly position the space anatomical position of the current section.
Preferably, the system further comprises:
and the setting module is arranged at the browser end and used for setting the threshold range of the image window width and window level.
Preferably, the system further comprises:
and the blood supply position determining module is used for determining the blood supply position of the branch blood vessel by taking the coordinates of the start point and the stop point of the aorta area as seed points and combining the threshold range set by the setting module at the browser end.
Therefore, the blood supply position of the branch blood vessel is acquired more accurately, and whether the branch blood vessel is supplied with blood from a true cavity or a false cavity is determined.
Preferably, the browser end and the background server end are in data communication in a base64 coding mode.
Preferably, the background server side adopts a django-socket frame, the ports of the background server adopt socket long connection, and the time for establishing and closing the connection is specified.
In the above, django is used for establishing network connection between the browser and the web background server and receiving and forwarding command parameters of interactive operation; the socket is used for establishing communication connection between the web background service and the 3D engine, inputting interactive command parameters and returning a processing result, and simultaneously controlling the life cycle of the memory area occupied by the three-dimensional reconstruction data.
In summary, the aorta three-dimensional reconstruction visualization system based on the B-S framework provided by the present application can realize the visualization presentation of the aorta image through three-dimensional reconstruction.
Drawings
Fig. 1 is a schematic structural diagram of an aorta three-dimensional reconstruction visualization system based on a B-S architecture according to an embodiment of the present application;
fig. 2 is a relational topology diagram of an architecture of a B-S architecture-based aorta three-dimensional reconstruction visualization system according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a three-dimensional vessel region fusion display provided by an embodiment of the present application;
FIG. 4 is a schematic diagram of a spatial orientation of a centerline of a lumen of interest of an aorta with a standard vertical plane, provided by an embodiment of the present application;
fig. 5 is a schematic diagram of a blood supply position of a branch blood vessel displayed by processing results under different threshold conditions provided by the embodiment of the application.
Detailed Description
The present application will be described below with reference to the drawings in the embodiments of the present application.
Example one
As shown in fig. 1, the present application provides a B-S architecture based aorta three-dimensional reconstruction visualization system, comprising:
the establishment of the three-terminal communication mechanism is performed first. As shown in fig. 2, the system architecture is divided into: the system comprises a browser end, a web background server end and a 3D algorithm engine end. The specific responsibilities are divided as follows:
the browser end adopts html + css + JavaScript language. The method is mainly used for interaction of mouse events, function switching and presentation of processing results. The processing result of each interaction is jpg picture, and the data communication of the front end and the back end is carried out in a base64 coding mode.
And the web background server side adopts a django + socket framework. The method is mainly used for connecting the browser end and the reconstruction algorithm layer and supporting data communication between the browser end and the reconstruction algorithm layer. Specifically, a mouse interaction instruction and a function switching instruction of a browser end are used as input parameters to be transmitted to a three-dimensional reconstruction algorithm; the processing result (mainly pictures) of the three-dimensional reconstruction algorithm is then returned to the browser end for presentation in the form of base64 code. The service interface uses socket long connections and should specify the timing of connection setup and shutdown.
The 3D algorithm engine end is constructed by adopting an Insight Segmentation and Registration Toolkit (ITK) and The Visualization Toolkit (VTK) algorithm package in combination with other graphic image processing toolkits. The method is mainly used for performing three-dimensional rendering processing on the original sequence according to the parameter input requirement, and storing the window image in the memory by adopting an OpenGL window off-screen rendering mode as a result. The ITK is used for reading the original sequence and constructing three-dimensional volume data, and the VTK is used for conducting graph rendering calculation on the three-dimensional volume data.
Specifically, the system comprises:
the acquiring module 101 is arranged at a browser end and used for receiving an aorta image three-dimensional reconstruction request and acquiring a CT sequence of an original aorta to be processed;
the first sending module 102 is arranged at the browser end and used for sending the request to the web background server end in an instruction form;
the transfer module 103 is arranged at the web background server end and used for receiving the instruction and transferring the instruction as an access parameter to the 3D algorithm engine end;
the image reconstruction module 104 is arranged at the 3D algorithm engine end and is used for performing 3D model reconstruction processing on the aorta according to the entry parameter;
wherein the image reconstruction module 104 comprises: the reading and constructing submodule is used for reading the original CT sequence of the aorta and constructing three-dimensional volume data; and the rendering submodule is used for performing three-dimensional rendering processing on the three-dimensional volume data according to the parameter input requirement. Wherein the three-dimensional rendering processing of the rendering sub-module includes: and combining the surface rendering result of the region of interest and the volume rendering result of the original region by adopting a rendering mode of combining surface rendering and volume rendering to obtain the 3D image model after three-dimensional rendering processing. The surface drawing result of the region of interest is combined with the volume drawing result of the original region, so that original information can be reserved to the maximum extent, the region of interest is highlighted, and the memory overhead burden of a server can be increased to the minimum extent.
Wherein, the image reconstruction module further comprises: the center line extraction submodule is used for extracting the center line of the blood vessel cavity; the fusion sub-module is used for fusing and displaying the blood vessel cavity central line and the 3D image model; the standard vertical plane generation submodule is used for generating a blood vessel standard vertical plane; and the positioning sub-module is used for providing space positioning of the standard vertical plane. The extracted blood vessel cavity central line and the 3D model are subjected to fusion display, and a space positioning function of a standard vertical plane is provided, so that a doctor can quickly position the space anatomical position of the current section while browsing the standard vertical plane of the aorta.
A second sending module 105, disposed at the 3D algorithm engine end, and configured to send the reconstructed 3D aorta model to the browser end;
and a rendering module 106, disposed at the browser end, for receiving and rendering the 3D aorta model after the reconstruction processing.
And the storage module 108 is used for storing the reconstructed aorta 3D model to a specified memory area.
Wherein, the system still includes:
the viewing module 109 is arranged at the browser end and is used for receiving different viewing requests and sending the requests to the background server end; the viewing request may be a viewing request of movement, rotation, zooming, color adjustment, transparency adjustment and the like of the corresponding aorta 3D model generated by mouse movement, sliding up and down and the like.
And a third sending module 110, disposed at the background server end, configured to call the corresponding aorta 3D model stored in the specified memory area according to the instruction, and send the aorta 3D model to the rendering module at the browser end.
Wherein, the system still includes:
the setting module 111 is disposed at the browser end and configured to set a threshold range of the image window width level.
Wherein, the system still includes:
and the blood supply position determining module 107 is used for determining the blood supply position of the branch blood vessel by taking the coordinates of the start point and the stop point of the aorta area as seed points and combining the threshold range set by the setting module at the browser end.
In order to more clearly illustrate the technical solution of the present application, the working principle of the system of the present application is described as follows:
the obtaining module 101 disposed at the browser end receives the aorta image three-dimensional reconstruction request and obtains a CT sequence of an original aorta to be processed, wherein an input type is a dicom image sequence, which includes original image data and intermediate data, and an input source is a segmentation result of an aorta blood vessel processed by a pre-segmentation algorithm.
The first sending module 102 is arranged at the browser end and used for sending the request to the web background server end in an instruction form;
the transfer module 103 is arranged at the web background server side and used for receiving the instruction and transferring the instruction as the access parameter to the 3D algorithm engine side;
an image reconstruction module 104 disposed at the 3D algorithm engine end performs 3D model reconstruction processing on the aorta according to the entry parameters, specifically: the reading and constructing sub-module reads the CT sequence of the original aorta and constructs three-dimensional volume data; for the segmentation result of the whole aorta and the interested cavity, the segmentation result is subjected to three-dimensional data fusion with the original image sequence and is displayed in a rendering mode, the result can be more visually embodied, a doctor can make a next operation scheme, and the method has certain clinical significance. Since the segmentation result of the input aorta is a set of mask sequences with the same number of layers and size as the original sequence, the format is also dicom format. If the volume rendering algorithm consistent with the original sequence is adopted for processing, double copies of memory data of the server side can be caused, and the improvement of later-period performance is not facilitated. In view of this, we propose a rendering scheme that merges surface rendering and volume rendering. Since the background area in the mask is represented by 0 and the different foreground areas are represented by the designated numbers, the region of interest is rendered in a face-drawn form by the marching cubes method. Since the result of surface rendering is primitive information, which is a topological structure, the amount of data required for storage is much smaller. However, compared with volume rendering, information of surface rendering is incomplete, and rendering effects have no sense of hierarchy. Therefore, the rendering submodule combines the surface rendering result of the region of interest with the volume rendering result of the original region, so that original information can be reserved to the maximum extent, the region of interest is highlighted, and the memory overhead burden of the server can be increased to the minimum extent. As shown in fig. 3 below, the original data is in a volume rendering mode, the aorta true lumen is in a black dot filling region (the black dot filling region may also be filled with a color, such as green) and the aorta false lumen is in a slash filling region (the slash filling region may also be filled with a color, such as orange), and the two are in a surface rendering mode, and the final result is a mixed mode.
Further, a central line extraction sub-module of the image reconstruction module extracts a central line of the blood vessel cavity; the fusion sub-module performs fusion display on the blood vessel cavity central line and the 3D image model; the standard vertical plane generation submodule generates a blood vessel standard vertical plane; the positioning sub-module provides spatial positioning of a standard vertical plane. The extracted blood vessel cavity central line and the 3D model are subjected to fusion display, and a space positioning function of a standard vertical plane is provided, so that a doctor can quickly position the space anatomical position of the current section while browsing the standard vertical plane of the aorta. Based on this, we combine the three-dimensional reconstructed 3D model with the spatial geometry model in the field of computer graphics for co-presentation. Wherein the spatial representation of the center line is embodied in a set of line elements and the spatial representation of the normal vertical plane position is embodied in one primitive. At the same time, the raw data is blurred to highlight the set of primitive systems, as shown in fig. 4. The middle white line expresses the centerline of the aortic lumen (here, the true lumen is taken as an example), and the black slice in the middle of the middle white line expresses the different cross-sectional positions of the aorta.
The second sending module 105 disposed at the 3D algorithm engine end sends the reconstructed 3D aorta model to the browser end (which is transmitted to the browser end in the form of a character stream via picture base64 encoding technology).
And a rendering module 106 arranged at the browser end and used for receiving the 3D aorta model after the reconstruction processing and decoding and rendering the 3D aorta model.
In a system of a B/S framework, interaction is initiated by a user from a browser end, the processing process is completed by a server end, and the processing result is presented again at the browser end.
The viewing module 109 arranged at the browser end receives different viewing requests and sends the requests to the background server end; the viewing request may be a viewing request of movement, rotation, zooming, color adjustment, transparency adjustment and the like of the corresponding aorta 3D model generated by mouse movement, sliding up and down and the like.
And a third sending module 110 disposed at the background server side, which calls the corresponding aorta 3D model stored in the specified memory area according to the instruction, and sends the aorta 3D model to a rendering module at the browser side.
In the process of making a clinical operation scheme, important information is to confirm whether branch blood vessels of each anatomical part supply blood in a true cavity or a false cavity after the aortic dissection is diseased. Based on this, we propose a solution combining the traditional image segmentation method with the AI segmentation algorithm to observe the processing result in real time. According to the blood vessel shape of the aorta, the upper and lower boundaries of the aorta in the z-axis direction of the dicom coordinate system can be determined by analyzing the mask sequence, then two-dimensional image connected domain analysis is carried out layer by layer, and the coordinates of the start point and the stop point of the aorta region can be confirmed. Taking the obtained data as a seed point, combining a threshold range dynamically set by a browser end by a user (the threshold range of an image window width window level is set by a setting module 111 arranged at the browser end, a blood supply position determining module arranged at an algorithm engine end takes the coordinates of the start point and the end point of the aorta area as the seed point, and combining the threshold range set by the setting module arranged at the browser end to determine the blood supply position of the branch blood vessel, a segmentation result can be obtained by using a traditional image segmentation algorithm, because the branch blood vessel connected with the aorta area has voxels with a similar CT value as the aorta area, the result of the traditional segmentation algorithm often contains the parts (even if under-segmentation or over-segmentation, the user can still make the threshold value be adjusted dynamically to a relatively satisfactory degree), and combining the result with the AI segmentation algorithm result, the requirement of identifying the branch blood vessel feeding cavity can be met. As shown in fig. 5, the results of the processing under different threshold conditions are shown. It can be seen from the figure that under different threshold conditions, the effect is different, and the threshold is dynamically adjusted to a relatively satisfactory degree, as can be clearly shown in a and c graphs in fig. 5 compared with b graphs, the three branches (the head and arm trunk, the left common carotid artery and the left subclavian artery) on the aortic arch supply blood to the true cavity (the cavity corresponding to the black dot filling area in the figure) (the black dot filling can also be represented by color filling, such as green).
In summary, the aorta three-dimensional reconstruction visualization system based on the B-S framework provided by the present application can realize the visualization presentation of the aorta image through three-dimensional reconstruction.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A B-S architecture based aorta three-dimensional reconstruction visualization system is characterized by comprising:
the acquisition module is arranged at the browser end and used for receiving an aorta image three-dimensional reconstruction request and acquiring an original aorta CT sequence to be processed;
the first sending module is arranged at the browser end and used for sending the request to the background server end in an instruction form;
the transmission module is arranged at the background server end and used for receiving the instruction and transmitting the instruction as an input parameter to the algorithm engine end;
the image reconstruction module is arranged at the algorithm engine end and used for performing aorta image three-dimensional reconstruction processing according to the entry parameter so as to obtain a reconstructed aorta 3D model;
the second sending module is arranged at the algorithm engine end and used for sending the reconstructed aorta 3D model to the browser end;
and the presentation module is arranged at the browser end and used for receiving and presenting the reconstructed aorta 3D model.
2. The system of claim 1, wherein the image reconstruction module comprises:
the reading and constructing submodule is used for reading the original CT sequence of the aorta and constructing three-dimensional volume data;
and the rendering submodule is used for performing three-dimensional rendering processing on the three-dimensional volume data according to the parameter input requirement.
3. The system of claim 2, further comprising:
and the storage module is arranged at the background server end and used for storing the reconstructed aorta 3D model to a specified memory area.
4. The system of claim 3, further comprising:
the viewing module is arranged at the browser end and used for receiving different viewing requests and sending the requests to the background server end;
and the third sending module is arranged at the background server end and used for calling the image of the corresponding aorta 3D model stored in the designated memory area according to the instruction and sending the image to the rendering module at the browser end.
5. The system of claim 4, wherein the three-dimensional rendering process of the rendering sub-module comprises:
and combining the surface rendering result of the region of interest and the volume rendering result of the original region by adopting a rendering mode of combining surface rendering and volume rendering to obtain the 3D aorta model after three-dimensional rendering processing.
6. The system of claim 5, wherein the image reconstruction module further comprises:
the center line extraction submodule is used for extracting the center line of the blood vessel cavity;
a fusion sub-module for fusion display of the vessel lumen centerline with the aorta 3D model;
the standard vertical plane generation submodule is used for generating a blood vessel standard vertical plane;
and the positioning sub-module is used for providing space positioning of the standard vertical plane.
7. The system of claim 1, further comprising:
and the setting module is arranged at the browser end and used for setting the threshold range of the image window width and window level.
8. The system of claim 7, further comprising:
and the blood supply position determining module is arranged at the algorithm engine end and is used for determining the blood supply position of the branch blood vessel by taking the coordinates of the start point and the stop point of the aorta area as seed points and combining a threshold range set by the setting module at the browser end.
9. The system of claim 1, wherein the browser end and the backend server end are in data communication in a form of base64 encoding.
10. The system of claim 1, wherein the backend server uses a django-socket framework, and a port of the backend server uses a socket long connection and specifies the time for establishing and closing the connection with the browser side.
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Address after: 100000 Zhongguancun Dongsheng Science Park, 66 xixiaokou Road, Haidian District, Beijing A206, 2f, building B-2, Northern Territory Applicant after: Huiying medical technology (Beijing) Co.,Ltd. Address before: 100192 A206, 2 / F, building B-2, Dongsheng Science Park, Zhongguancun, 66 xixiaokou Road, Haidian District, Beijing Applicant before: HUIYING MEDICAL TECHNOLOGY (BEIJING) Co.,Ltd. |
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