Real-time imaging dynamic navigation system for breast tumor interventional operation

Abstract

The invention discloses a real-time imaging dynamic navigation system for a breast tumor interventional operation, which comprises an acousto-optic scanning device, a Redis client, a Redis server, a database, a modeling platform, a Three.js dynamic driving engine and a display terminal, and is characterized in that the acousto-optic scanning device is arranged above a breast tumor and performs scanning and data acquisition in a non-contact manner during the operation; the Redis client, the Redis server and the database respectively acquire, distribute and store the acquired data, and the modeling platform performs model construction on the received data. A Three.js dynamic driving engine composed of a breast tumor data input end, an initial data driving unit, an incremental data driving unit, a rendering unit and a dynamic image output end carries out data processing on the model in a data driving mode. According to the dynamic navigation system, real-time data acquisition, transmission and data processing are realized, the generated navigation image is visual and dynamic, high-quality image guidance is provided for an operation, and the success rate and accuracy of the operation are improved.

Description

Technical Field

[0001] The invention belongs to the technical field of data processing, and in particular, relates to a real-time imaging dynamic navigation system for breast tumor intervention surgery. Background Art

[0002] Interventional surgery for breast tumors is a minimally invasive treatment method that uses precision instruments such as catheters to directly deliver drugs to the tumor site, perform embolization, or apply physical ablation methods under preoperative and intraoperative image guidance to achieve the purpose of directly killing solid tumors. This method does not require surgery, has less trauma, and reduces damage to surrounding normal tissues. Preoperative image guidance usually uses B-ultrasound, CT, and MRI preoperative imaging data to obtain information such as the size, shape, location, and boundaries of the breast tumor to determine the scope and staging of the operation, thereby formulating a reasonable preoperative treatment plan; intraoperative image guidance usually uses B-ultrasound imaging guidance to assist the implementation of the operation. Preoperative and intraoperative images serve as a guide for surgery. However, during the formal surgical operation, the current breast tumor condition has changed due to the patient's current condition and real-time changes in breast morphology. Previous imaging data can no longer reflect the current breast tumor condition in real time. Intraoperative B-ultrasound images are limited by probe contact operation and prevention of wound infection, and cannot fully collect data in real time and dynamically. This static image not only cannot achieve real-time synchronization in the true sense, but B-ultrasound images also have limitations in identifying breast tumor boundaries and deep tissues.

[0003] In the prior art, the patent with the patent publication number CN118490354A records a real-time image navigation system and related devices for breast tumor surgery. The patent uses image fusion technology to fuse MRI breast tumor images, CT breast tumor images and B-ultrasound breast tumor images collected before surgery to generate a comprehensive breast tumor image. At the same time, the patent collects breast tumor images by B-ultrasound during the operation to assist the implementation of the operation. This comprehensive breast tumor image and the breast tumor image collected by B-ultrasound are helpful for analyzing the location and state of the breast tumor. However, the comprehensive breast tumor image of the patent is data collected before surgery, not real-time data collection during surgery. At the same time, the intraoperative B-ultrasound image is limited by the contact operation of the ultrasound probe, and cannot achieve the effect of real-time synchronization during surgery, and cannot provide accurate and intuitive dynamic navigation images, which in turn affects the success rate and accuracy of the operation. Therefore, there is an urgent need for a dynamic navigation system that can accurately collect data in real-time synchronization during surgery and intuitively display breast tumor images. Summary of the invention

[0004] In order to overcome the above-mentioned deficiencies in the prior art, the present invention provides a dynamic navigation system for breast tumor interventional surgery, which adopts an acoustic-optical scanning device to synchronously and accurately collect breast tumor data in real time during the operation, and generates intuitive breast tumor images through real-time transmission, distribution, storage, modeling, and data-driven of the data.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] A real-time imaging dynamic navigation system for breast tumor intervention surgery, comprising an acoustic-optical scanning device for collecting data on breast tumors, a Redis client for acquiring data collected by the acoustic-optical scanning device, a Redis server for distributing data from the Redis client, a database for storing data from the Redis server, a modeling platform for modeling the data from the Redis server, a Three.js dynamic driving engine for data driving and image rendering in combination with the modeling platform and the data from the database, and a display terminal for displaying a dynamic navigation image of a breast tumor generated by the Three.js dynamic driving engine, wherein:

[0007] The Three.js dynamic driving engine includes a breast tumor data input end connected to both the modeling platform and the database, an initial data driving unit connected to the breast tumor data input end, an incremental data driving unit connected to the initial data driving unit, a rendering unit connected to the incremental data driving unit, and a dynamic image output end connected to the rendering unit, wherein the rendering unit is connected to the initial data driving unit, and the dynamic image output end is connected to the display terminal.

[0008] Furthermore, the initial data driving unit includes a data verification module connected to the breast tumor data input end, a data flow monitoring module and a historical data evolution module connected to the data verification module, a data flow acquisition module connected to the data flow monitoring module, and a model comparison and judgment module connected to the data flow acquisition module, wherein the historical data evolution module is connected to the data flow monitoring module.

[0009] Furthermore, the incremental data driving unit includes a cumulative storage incremental module connected to the model comparison judgment module, an incremental threshold judgment module connected to the cumulative storage incremental module, and a reset storage data module connected to the incremental threshold judgment module, wherein the reset storage data module is connected to the rendering unit.

[0010] Furthermore, the rendering unit includes a coloring module for setting the color of the breast tumor image according to different biological components through the color attribute of the Three.js tool.

[0011] Furthermore, the rendering unit includes a rotation module that uses the position attribute of the Three.js tool to rotate the breast tumor image.

[0012] Furthermore, the rendering unit includes a transparency setting module for performing transparency processing on the non-breast tumor biological tissue image through the opacity option of the Three.js tool.

[0013] Furthermore, the modeling platform is connected to a lightweight processing module for reducing the weight of the constructed model.

[0014] Furthermore, the Redis client obtains the data transmitted by the acoustic and optical scanning device in real time through the RS485 communication interface.

[0015] Furthermore, the Redis client, Redis server, database, modeling platform, Three.js dynamic drive engine, and display terminal communicate data with each other based on the ProfiNet communication protocol.

[0016] Furthermore, the acousto-optic scanning device includes a scanning mirror for real-time scanning of breast tumors, an optical exciter and an ultrasonic array connected to the scanning mirror, a data collector connected to the ultrasonic array, and a data transmission module connected to the data collector, wherein the data transmission module is connected to the Redis client.

[0017] Compared with the prior art, the present invention has the following beneficial effects:

[0018] (1) The present invention not only realizes real-time synchronous data collection of breast tumors during surgery through the acoustic and optical scanning device, but also overcomes the limitations of B-ultrasound images in identifying breast tumor boundaries and deep tissues through the acoustic and optical scanning method, making the collected data more accurate. By setting up a Redis client, a Redis server, and a database to respectively acquire, distribute, and store the collected breast tumor data, a real-time high-speed data acquisition and transmission network is formed, which can acquire data once, distribute data multiple times, and be reused. In addition, the Redis client and the Redis server have a fast data parsing speed, which ensures the real-time nature of the data. After the model is built on the modeling platform, the initial data driving unit and the incremental data driving unit in the Three.js dynamic driving engine complete the data processing of the dynamic image in a data-driven manner, and the rendering unit performs rendering and highlighting operations to enhance the visualization effect. Through intuitive and dynamic navigation images, high-quality image guidance is provided for surgery, making the surgical operation more accurate and improving the surgical efficiency and success rate.

[0019] (2) The initial data driving unit of the present invention realizes the driving of the model by the initial data through the setting of the data verification module, the data flow monitoring module, the historical data evolution module, the data flow acquisition module, and the model comparison and judgment module, thereby ensuring the accuracy of the initial image. At the same time, the incremental data driving unit completes the incremental data driving through the cumulative storage incremental module, the incremental threshold judgment module, and the reset storage data module, thereby realizing the intuitive display of the dynamic changes of breast tumors during surgery. This data processing method based on real-time data driving the model not only improves the data processing efficiency, but also further improves the output image quality.

[0020] (3) The coloring module of the present invention realizes the coloring processing of the breast tumor image according to the different biological components through the color attribute of the Three.js tool, so that the breast tumor is more prominently displayed. The rotation module uses the position attribute of the Three.js tool to rotate the breast tumor image. By rotating the breast tumor image, the observation angle of the breast tumor is increased. The transparency setting module uses the opacity option of the Three.js tool to make the non-breast tumor biological tissue image transparent, further enhancing the prominent display of the breast tumor. The breast tumor image after the rendering operation of coloring, rotation, and transparency setting is more intuitive, and the navigation effect is enhanced.

[0021] (4) The lightweight processing module of the present invention reduces the consumption of computing resources by the system through lightweight processing of the constructed model, avoids the delay of data processing caused by overly complex calculations, and ensures the real-time output of dynamic images.

[0022] (5) The Redis client of the present invention obtains the data transmitted by the sound and light scanning device in real time through the RS485 communication interface, thereby ensuring the real-time transmission of data. In addition, the Redis client, Redis server, database, modeling platform, Three.js dynamic drive engine, and display terminal mutually construct a high-precision closed-loop data communication system through the ProfiNet communication protocol, thereby further enhancing the real-time performance and data security of data transmission.

[0023] (6) The acousto-optic scanning device of the present invention includes a scanning mirror, an optical exciter, an ultrasonic array, a data acquisition device, and a data transmission module. The scanning mirror is placed above the breast tumor and scans it in a non-contact manner during surgery. Since each basic biological component has a different optical absorption spectrum, not only rapid imaging during surgery is achieved, but the acousto-optic scanning method also provides information-rich optical contrast, thereby improving imaging resolution and imaging depth, and further improving imaging quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic diagram of the composition principle of the real-time imaging dynamic navigation system of the present invention;

[0025] Figure 2 This is a schematic diagram of the composition principle of the Three.js dynamic drive engine of the present invention;

[0026] Figure 3 It is a schematic diagram of the composition of the rendering unit of the real-time imaging dynamic navigation system of the present invention;

[0027] Figure 4 A schematic diagram of the process of data processing performed by the Three.js dynamic driving engine of the present invention;

[0028] Figure 5 It is a schematic diagram comparing the cross-sectional imaging quality of the acoustic-optical scanning of the present invention and the traditional imaging.

[0029] In the above drawings, the component names corresponding to the reference numerals are as follows:

[0030] 1-acoustic-optical scanning device, 2-Redis client, 3-Redis server, 4-database, 5-modeling platform, 6-lightweight processing module, 7-Three.js dynamic driving engine, 8-display terminal, 101-scanning mirror, 102-optical exciter, 103-ultrasonic array, 104-data collector, 105-data transmission module, 701-breast tumor data input terminal, 702-initial data driving unit, 703-incremental data driving unit, 704-rendering unit, 705-dynamic image output terminal, 702a-data verification module, 702b-historical data evolution module, 702c-data flow monitoring module, 702d-data flow acquisition module, 702e-model comparison judgment module, 703a-accumulated storage increment module, 703b-increment threshold judgment module, 703c-reset storage data module, 704a-coloring module, 704b-rotation module, 704c-transparency setting module. DETAILED DESCRIPTION

[0031] The present invention is further described below in conjunction with the accompanying drawings and examples. The embodiments of the present invention include but are not limited to the following examples.

[0032] Example

[0033] like Figure 1-Figure 5 As shown, this embodiment provides a real-time imaging dynamic navigation system for breast tumor interventional surgery, including an acoustic-optical scanning device 1, a Redis client 2, a Redis server 3, a database 4, a modeling platform 5, a Three.js dynamic drive engine 7, and a display terminal 8, wherein the acoustic-optical scanning device 1 is placed above the breast tumor to perform scanning and data collection in a non-contact manner during surgery. Compared with intraoperative B-ultrasound imaging, which is limited by probe contact operation and prevention of wound infection, this real-time dynamic data collection method realizes true synchronous image guidance during surgery, and the new imaging method of acoustic-optical imaging provides information-rich optical contrast. According to the different optical absorption spectra of each basic biological component in the breast tumor, the acoustic-optical scanning device 1 adjusts the emitted light into multiple wavelengths, and hemoglobin, melanin, water, myoglobin, nucleic acid, and fat can all be endogenously mapped and imaged. Acoustic-optical imaging has advantages in identifying the boundaries and deep tissues of breast tumors, overcoming the limitations of B-ultrasound imaging, such as Figure 5 As shown, a and c are schematic diagrams of the cross-sectional imaging quality of acoustic and optical scanning, and b and d are schematic diagrams of the cross-sectional imaging quality of traditional imaging B-ultrasound, CT, and MRI. Compared with traditional imaging methods, the quality of acoustic and optical imaging is better.

[0034] Redis in the Redis client 2 and the Redis server 3 of this embodiment is the abbreviation of Remote Dictionary Server in English, and its Chinese name is Remote Dictionary Service. Redis is an open source memory data structure storage system, which uses memory as the main storage medium, has multiple data types, and is widely used for data acquisition, caching, and distribution. After the sound and light scanning device 1 collects data, it can transmit the data to the Redis client 2 in real time, and the Redis client 2 then sends the data to the Redis server 3 for data distribution. The database 4 of this embodiment adopts the GoldenDB database, which is a domestic independently developed database with the advantages of light weight, high speed, stability and cross-platform, and the database is open source to ensure data security and low cost. The Redis client 2 and the Redis server 3 of this embodiment can be deployed locally or remotely according to actual needs. The Redis client 2 and the Redis server 3 have a fast data parsing speed, and local or remote deployment can ensure the real-time nature of the data. The Redis client 2, the Redis server 3, and the database 4 respectively acquire, distribute, and store the collected breast tumor data, forming a real-time high-speed data acquisition and transmission network that can acquire data once, distribute multiple times, and can be reused.

[0035] The modeling platform 5 of this embodiment adopts the WebGL platform. WebGL is the abbreviation of Web Graphics Library in English, and its Chinese meaning is network graphics library. WebGL is a 3D drawing protocol. After receiving the breast tumor data from the Redis server, the WebGL platform performs modeling operations according to the modeling instructions. The three-dimensional model constructed by the WebGL platform cannot respond to the changes of the breast tumor during surgery in real time. Then, the Three.js dynamic driving engine 7 is used to drive the constructed model according to the real-time collected breast tumor data, so as to truly realize the real-time and synchronization of the generated image and dynamically respond to the changes of the breast tumor during surgery. Three.js is a powerful graphics data processor based on the JavaScript programming language. It can realize high-quality three-dimensional graphics driving and rendering through a simple application program interface. Through the connection with the database 4, Three.js can drive the three-dimensional model with the collected data in real time, so that the model can dynamically reflect the state changes of the breast tumor. At the same time, by adopting the tool component of Three.js, the breast tumor image is further rendered to better observe the breast tumor.

[0036] In this embodiment, the Three.js dynamic driving engine 7 includes a breast tumor data input terminal 701, an initial data driving unit 702, an incremental data driving unit 703, a rendering unit 704, and a dynamic image output terminal 705, wherein the breast tumor data input terminal 701 is connected to the modeling platform 5 to obtain model data from the modeling platform 5, and the breast tumor data input terminal 701 is also connected to the database 4 to obtain real-time and historical data of breast tumors from the database 4. The breast tumor data input terminal 701 transmits the acquired data to the initial data driving unit 702 to complete the initial image generation before the breast tumor state changes. During the implementation of the operation, the state of the breast tumor changes. The incremental data drives the initial image generated by the initial data driving unit 702 through the incremental data driving unit 703, thereby generating an image after the state change. The rendering unit 704 further renders the images generated by the initial data driving unit 702 and the incremental data driving unit 703. The rendered dynamic navigation image of the breast tumor is finally displayed through the display terminal 8. By comparing the rendered images generated by the initial data driving unit 702 and the incremental data driving unit 703, the dynamic changes in the condition of the breast tumor during the operation can be clearly and intuitively reflected, so as to dynamically navigate the implementation process of the operation.

[0037] The initial data driving unit 702 of this embodiment includes a data verification module 702a, a data flow monitoring module 702c, a historical data evolution module 702b, a data flow acquisition module 702d, and a model comparison and judgment module 702e. The data verification module 702a verifies the data accuracy of the acquired breast tumor data. If the data is inaccurate, the historical data evolution module 702b is used for data comparison. The data flow monitoring module 702c monitors the overall data flow of the judged data to determine whether the data flow is running normally. Specifically, it depends on whether the data is missing. Missing data causes an abnormal alarm to be sent. If the data is not missing, it runs normally. After acquiring the data flow, the data flow acquisition module 702d performs model comparison through the model comparison and judgment module 702e, thereby generating comparison data and updating the model data. The accuracy of the initial image is guaranteed through the operation of each module.

[0038] The incremental data driving unit 703 of this embodiment includes a cumulative storage increment module 703a, an incremental threshold judgment module 703b, and a reset storage data module 703c, wherein the cumulative storage increment module 703a accumulates and stores the acquired incremental breast tumor data, and the incremental threshold judgment module 703b is used to judge whether the storage increment is greater than a preset threshold. When the increment is not greater than the threshold, the original data is maintained, and when the increment is greater than the threshold, the incremental data is stored, and then a new image is generated by resetting the storage data module 703c. While ensuring the real-time nature of the image, this embodiment also considers optimizing the operating performance of the system and reducing the frequency of image updates. By comparing the incremental data with the threshold, it is judged whether the image needs to be updated. In practice, the threshold is lowered as much as possible to increase the update frequency of the model.

[0039] In this embodiment, the rendering unit 704 renders the breast tumor image generated by the initial data driving unit 702 and the incremental data driving unit 703. The rendering unit 704 includes a coloring module 704a, a rotation module 704b, and a transparency setting module 704c. The coloring module 704a sets the color of the breast tumor image according to different biological components in the breast tumor. Specifically, different colors are set for biological components such as hemoglobin, melanin, water, myoglobin, nucleic acid, and fat through the color attribute of the Three.js tool, thereby enhancing the visualization observation effect; the rotation module 704b uses the position attribute of the Three.js tool to rotate the breast tumor image. By rotating the breast tumor image, the observation angle of the breast tumor is increased; the transparency setting module 704c uses the opacity option of the Three.js tool to make the non-breast tumor biological tissue image transparent, and the image after transparency processing further enhances the highlighting of the breast tumor.

[0040] There are many biological components inside breast tumors. In order to avoid the complicated process of repeated modeling and to avoid increasing the complexity of calculation and the consumption of system resources, while highlighting the key features of breast tumor images, this embodiment sets a lightweight processing module 6 to perform lightweight processing during the modeling process of the modeling platform 5. In the specific implementation, the Blender tool is used to delete some biological tissues around the breast tumor in the model, such as fat, water, etc. The Blender tool is a powerful model processing software that provides rich components to achieve lightweight models.

[0041] In this embodiment, the Redis client 2 obtains the data transmitted by the sound and light scanning device 1 in real time through the RS485 communication interface. RS485 is a communication protocol standard with the advantages of simple interface structure, high transmission rate, low cost, and easy installation. The RS485 communication interface data transmission rate adopted in this embodiment can reach up to 10Mbps, which ensures the real-time transmission of data. The Redis client 2, Redis server 3, database 4, modeling platform 5, Three.js dynamic drive engine 7, and display terminal 8 in this embodiment mutually build a high-precision closed-loop data communication system through the ProfiNet communication protocol. ProfiNet is an Ethernet-based communication transmission protocol. ProfiNet can provide deterministic and isochronous transmission time key process data in applications, with a jitter of less than 1 microsecond. At the same time, ProfiNet integrates PROFIsafe functional safety technology, allowing the same cable to be used for standard and safety-related communications, simplifying the system architecture and meeting strict safety standards. The adoption of the ProfiNet communication protocol further enhances the real-time and data security of data transmission of this real-time imaging dynamic navigation system.

[0042] In this embodiment, the acousto-optic scanning device 1 includes a scanning mirror 101, an optical exciter 102, an ultrasonic array 103, a data collector 104, and a data transmission module 105, wherein the scanning mirror 101 is placed above the breast tumor and scans in a non-contact manner during surgery, the light generated by the optical exciter 102 is irradiated to the biological tissue of the breast tumor through the scanning mirror 101, the light absorption domain of the biological tissue generates ultrasonic signals, the ultrasonic array 103 receives and records these ultrasonic signals, the data collector 104 collects the ultrasonic signals of the ultrasonic array 103 in real time, and the data transmission module 105 transmits the collected signals. This embodiment can further improve the data collection capability by increasing the scale of the ultrasonic array and increasing the number of channels in the data collector.

[0043] When the present invention is used, the breast tumor is first scanned by the acoustic-optical scanning device 1 to collect breast tumor data, and then the collected breast tumor data is acquired, distributed, and stored by the Redis client 2, the Redis server 3, and the database 4, and then the model is built by the modeling platform 5. Then, the initial data driving unit 702 and the incremental data driving unit 703 in the Three.js dynamic driving engine 7 complete the data processing of the dynamic image in a data-driven manner and perform the rendering operation through the rendering unit 704. Finally, the dynamic navigation image of the breast tumor is displayed through the display terminal 8. The present invention collects the breast tumor data in a non-contact manner during the operation by means of acoustic-optical scanning. Breast tumor data not only overcomes the limitation of B-ultrasound imaging on probe contact operation, realizes real-time dynamic data collection, achieves real-time synchronization, but also overcomes the limitations of B-ultrasound imaging in breast tumor boundary and deep tissue identification, improves the quality of collected data, and the data transmission network composed of Redis client 2, Redis server 3, and database 4 realizes real-time acquisition, distribution, and storage of collected data, provides support for modeling and generation of dynamic navigation images of breast tumors, and the accurate and intuitive dynamic navigation images generated by the dynamic navigation system of the present invention provide high-quality image guidance for surgery, improving the success rate and accuracy of surgery. The deployment and connection of the acoustic and optical scanning device 1, Redis client 2, Redis server 3, database 4, modeling platform 5, Three.js dynamic drive engine 7, display terminal 8, and lightweight processing module 6 in this embodiment can be realized by existing conventional software and hardware design, and its specific software settings and circuit structure are not repeated in this embodiment.

[0044] The above embodiments are only preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any changes made by adopting the design principles of the present invention and performing non-creative work on this basis should fall within the protection scope of the present invention.

Claims

1. A real-time imaging dynamic navigation system for breast tumor intervention surgery, characterized in that: The invention comprises an acoustic-optical scanning device (1) for collecting data on breast tumors, a Redis client (2) for acquiring data collected by the acoustic-optical scanning device (1), a Redis server (3) for distributing data from the Redis client (2), a database (4) for storing data from the Redis server (3), a modeling platform (5) for modeling the data of the Redis server (3), a Three.js dynamic driving engine (7) for combining the data of the modeling platform (5) and the database (4) for data driving and image rendering, and a display terminal (8) for displaying a dynamic navigation image of a breast tumor generated by the Three.js dynamic driving engine (7), wherein: The Three.js dynamic driving engine (7) comprises a breast tumor data input terminal (701) connected to both the modeling platform (5) and the database (4), an initial data driving unit (702) connected to the breast tumor data input terminal (701), an incremental data driving unit (703) connected to the initial data driving unit (702), a rendering unit (704) connected to the incremental data driving unit (703), and a dynamic image output terminal (705) connected to the rendering unit (704), wherein the rendering unit (704) is connected to the initial data driving unit (702), and the dynamic image output terminal (705) is connected to the display terminal (8).

2. A real-time imaging dynamic navigation system for breast tumor interventional surgery according to claim 1, characterized in that: The initial data driving unit (702) comprises a data verification module (702a) connected to the breast tumor data input terminal (701), a data flow monitoring module (702c) and a historical data evolution module (702b) connected to the data verification module (702a), a data flow acquisition module (702d) connected to the data flow monitoring module (702c), and a model comparison and judgment module (702e) connected to the data flow acquisition module (702d), wherein the historical data evolution module (702b) is connected to the data flow monitoring module (702c).

3. A real-time imaging dynamic navigation system for breast tumor interventional surgery according to claim 2, characterized in that: The incremental data driving unit (703) includes an accumulative storage incremental module (703a) connected to the model comparison judgment module (702e), an incremental threshold judgment module (703b) connected to the accumulative storage incremental module (703a), and a reset storage data module (703c) connected to the incremental threshold judgment module (703b), wherein the reset storage data module (703c) is connected to the rendering unit (704).

4. A real-time imaging dynamic navigation system for breast tumor interventional surgery according to claim 3, characterized in that: The rendering unit (704) includes a coloring module (704a) for setting the color of the breast tumor image according to different biological components through the color attribute of the Three.js tool.

5. The real-time imaging dynamic navigation system for breast tumor interventional surgery according to claim 3, characterized in that: The rendering unit (704) includes a rotation module (704b) for performing a rotation operation on the breast tumor image using the position attribute of the Three.js tool.

6. The real-time imaging dynamic navigation system for breast tumor interventional surgery according to claim 3, characterized in that: The rendering unit (704) includes a transparency setting module (704c) for performing transparency processing on the non-breast tumor biological tissue image through the opacity option of the Three.js tool.

7. The real-time imaging dynamic navigation system for breast tumor interventional surgery according to claim 1, characterized in that: The modeling platform (5) is connected to a lightweight processing module (6) for reducing the weight of the constructed model.

8. The real-time imaging dynamic navigation system for breast tumor interventional surgery according to claim 1, characterized in that: The Redis client (2) acquires the data transmitted by the acoustic and optical scanning device (1) in real time via the RS485 communication interface.

9. A real-time imaging dynamic navigation system for breast tumor interventional surgery according to claim 8, characterized in that: The Redis client (2), the Redis server (3), the database (4), the modeling platform (5), the Three.js dynamic drive engine (7), and the display terminal (8) perform data communication with each other based on the ProfiNet communication protocol.

10. A real-time imaging dynamic navigation system for breast tumor interventional surgery according to any one of claims 1 to 9, characterized in that: The acousto-optic scanning device (1) comprises a scanning mirror (101) for real-time scanning of breast tumors, an optical exciter (102) and an ultrasonic array (103) connected to the scanning mirror (101), a data collector (104) connected to the ultrasonic array (103), and a data transmission module (105) connected to the data collector (104), wherein the data transmission module (105) is connected to the Redis client (2).

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