Automatic data acquisition and standardization processing platform based on multi-mode ophthalmologic equipment

Abstract

The invention discloses a data automatic acquisition and standardization processing platform based on multi-mode ophthalmology equipment, and relates to the technical field of ophthalmology diagnosis and treatment, the data automatic acquisition and standardization processing platform comprises an equipment end, the output end of the equipment end is connected with an interface protocol converter, and the output end of the interface protocol converter is connected with an automatic trigger acquisition unit; and the output end of the automatic trigger acquisition unit is connected with a format conversion unit for converting formats. When the automatic data acquisition and standardization processing platform based on the multi-modal ophthalmologic equipment is used, firstly, interface protocols of multiple equipment can be converted through the interface protocol converter, so that real-time synchronization and conjoint analysis of cross-equipment data are supported, and the data are converted into a uniform data format through the format conversion unit; the method comprises the steps that firstly, data are acquired, then the data are preprocessed, so that the research consistency and accuracy are ensured, finally, the effect of automatically labeling a lesion area can be achieved through an AI auxiliary labeling unit, manual intervention is reduced, and the data acquisition and processing efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of ophthalmic diagnosis and treatment technology, and specifically to an automatic data acquisition and standardized processing platform based on multimodal ophthalmic equipment. Background Art

[0002] Ophthalmology is a professional medical discipline that studies the eyes and related diseases. It involves the diagnosis, treatment and prevention of visual system functions. Multimodal ophthalmic equipment is needed in the process of ophthalmic diagnosis and treatment. Therefore, multimodal ophthalmic equipment (such as fundus cameras, corneal topographers, etc.) has been widely used in clinical practice.

[0003] The existing automatic data collection and standardized processing platform for ophthalmic equipment leads to data silos when in use due to the closed equipment manufacturer's protocols, high algorithm heterogeneity and lack of an automation framework: the data output formats of different devices are not unified, making cross-platform integration and analysis difficult; there is a high degree of manual dependence: data needs to be manually labeled, classified and stored after collection, which is inefficient and prone to errors; lack of standardization: the lack of a unified preprocessing process leads to uneven data quality, affecting subsequent diagnosis and research; lack of real-time performance: the existing system finds it difficult to achieve synchronous collection and real-time processing of multimodal data. Summary of the Invention

[0004] The purpose of the present invention is to provide a data automatic collection and standardization processing platform based on multimodal ophthalmic equipment to solve the problems of data silos, high manual dependence, lack of standardization and insufficient real-time performance in the existing data automatic collection and standardization processing platform of multimodal ophthalmic equipment proposed in the above background technology.

[0005] To achieve the above-mentioned object, the present invention provides the following technical solution: an automatic data acquisition and standardization processing platform based on multimodal ophthalmic equipment, comprising: a device end, wherein the output end of the device end is connected to an interface protocol converter;

[0006] The output end of the interface protocol converter is connected to an automatic trigger acquisition unit, the output end of the automatic trigger acquisition unit is connected to a format conversion unit for converting the format, the output end of the format conversion unit is connected to a data preprocessing unit for preprocessing data, and the output end of the data preprocessing unit is connected to an AI-assisted labeling unit.

[0007] Preferably, the output end of the AI-assisted labeling unit is connected to a distributed database, and the output end of the distributed database is respectively connected to a RESTful API interface and a visual data dashboard.

[0008] Preferably, the equipment end includes a slit lamp, a biometer, a computer ophthalmometer, a tonometer, a comprehensive ophthalmometer, a corneal topographer, a fundus camera and a corneal endothelial cell counter.

[0009] Preferably, the device end and the interface protocol converter are both hardware modules.

[0010] Preferably, the automatic triggering acquisition unit includes a structured text data acquisition unit, an image data acquisition unit, a video data acquisition unit and a text report acquisition unit.

[0011] Preferably, the data preprocessing unit includes a denoising processing unit, a normalization processing unit and a registration processing unit.

[0012] Preferably, the automatic triggering acquisition unit, format conversion unit, data preprocessing unit and AI-assisted labeling unit all belong to the standardization processing module.

[0013] Preferably, the distributed database, RESTful API interface and visual data dashboard all belong to the storage and application modules.

[0014] Preferably, the interface protocol converter includes multiple communication interfaces such as DICOM, HL7, RS232, HTTPS, etc.

[0015] Preferably, the AI-assisted labeling unit automatically labels the lesion area mainly based on a deep learning model.

[0016] Compared with the existing technology, the beneficial effects of the present invention are: when the data automatic acquisition and standardized processing platform based on multimodal ophthalmic equipment is in use, the interface protocols of multiple devices can be converted through the interface protocol converter, thereby supporting real-time synchronization and joint analysis of cross-device data, and converted into a unified data format through the format conversion unit, and then the data is pre-processed to ensure research consistency and accuracy. Finally, the AI-assisted labeling unit can realize the function of automatically labeling the lesion area, thereby reducing manual intervention and improving data acquisition and processing efficiency. This is the use feature of the data automatic acquisition and standardized processing platform based on multimodal ophthalmic equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a schematic diagram of the system architecture structure of the present invention;

[0018] Figure 2 It is a schematic structural diagram of the working principle of the present invention.

[0019] In the figure: 1. Device end; 2. Interface protocol converter; 3. Automatic trigger acquisition unit; 4. Format conversion unit; 5. Data preprocessing unit; 6. AI-assisted annotation unit; 7. Distributed database; 8. RESTful API interface; 9. Visual data dashboard; 101. Slit lamp; 102. Biometer; 103. Computer ophthalmometer; 104. Tonometer; 105. Comprehensive ophthalmometer; 106. Corneal topographer; 107. Fundus camera; 108. Corneal endothelial cell counter; 10. Hardware module; 301. Structured text data acquisition unit; 302. Image data acquisition unit; 303. Video data acquisition unit; 304. Text report acquisition unit; 501. Denoising processing unit; 502. Normalization processing unit; 503. Registration processing unit; 11. Standardization processing module; 12. Storage and application module. DETAILED DESCRIPTION

[0020] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0021] See also Figure 1 and Figure 2 , the present invention provides a technical solution: a data automatic acquisition and standardization processing platform based on multimodal ophthalmic equipment, comprising: a device end 1, an output end of the device end 1 is connected to an interface protocol converter 2;

[0022] exist Figure 1 In the figure, the output end of the interface protocol converter 2 is connected to the automatic trigger acquisition unit 3, the output end of the automatic trigger acquisition unit 3 is connected to the format conversion unit 4 for converting the format, the output end of the format conversion unit 4 is connected to the data preprocessing unit 5 for preprocessing the data, and the output end of the data preprocessing unit 5 is connected to the AI ​​assisted labeling unit 6.

[0023] This data automatic acquisition and standardized processing platform based on multimodal ophthalmic equipment can convert the heterogeneous data collected by the automatic triggering acquisition unit 3 into a unified format (such as JSON+PNG+PDF) through the format conversion unit 4, and then pre-process the data. After processing, the AI-assisted annotation unit 6 automatically annotates the lesion area.

[0024] exist Figure 1 In the figure, the output end of the AI-assisted annotation unit 6 is connected to the distributed database 7, and the output end of the distributed database 7 is respectively connected to the RESTful API interface 8 and the visual data dashboard 9.

[0025] The data automatic acquisition and standardized processing platform based on multimodal ophthalmic equipment uses a distributed database to store data, thereby facilitating users to efficiently store and retrieve data, and then outputs data through a visual interface (such as a visual data dashboard 9) or API.

[0026] exist Figure 1 In the figure, the device end 1 includes a slit lamp 101, a biometer 102, a computer ophthalmometer 103, a tonometer 104, a comprehensive ophthalmometer 105, a corneal topographer 106, a fundus camera 107 and a corneal endothelial cell counter 108. The device end 1 and the interface protocol converter 2 both belong to the hardware module 10.

[0027] The data automatic acquisition and standardized processing platform based on multimodal ophthalmic equipment can unify the interface protocols of multimodal devices through the interface protocol converter 2, thereby supporting real-time synchronization and joint analysis of cross-device data.

[0028] exist Figure 1 In the figure, the automatic triggering acquisition unit 3 includes a structured text data acquisition unit 301, an image data acquisition unit 302, a video data acquisition unit 303 and a text report acquisition unit 304, the data preprocessing unit 5 includes a denoising processing unit 501, a normalization processing unit 502 and a registration processing unit 503, and the automatic triggering acquisition unit 3, the format conversion unit 4, the data preprocessing unit 5 and the AI ​​assisted annotation unit 6 all belong to the standardization processing module 11.

[0029] This data automatic acquisition and standardized processing platform based on multimodal ophthalmic equipment can collect data such as text data, image data, video data, and text reports by automatically triggering the acquisition unit 3, and then preprocess the data through the data preprocessing unit 5. Through the algorithm flow of the standardized processing module 11, the data format can be unified to ensure the consistency of the research.

[0030] exist Figure 1 In the example, the distributed database 7, the RESTful API interface 8 and the visual data dashboard 9 all belong to the storage and application module 12.

[0031] The data automatic acquisition and standardized processing platform based on multimodal ophthalmic equipment uses a distributed database 7 to store data, facilitates data storage and retrieval, and provides an API for third-party system calls.

[0032] exist Figure 1 In the embodiment, the interface protocol converter 2 includes multiple communication interfaces such as DICOM, HL7, RS232, and HTTPS.

[0033] The data automatic acquisition and standardization processing platform based on multimodal ophthalmic equipment can convert multiple different interface protocols to each other through the interface protocol converter 2, thereby realizing real-time synchronization of multimodal equipment data.

[0034] exist Figure 1 and Figure 2 In the

[15] , the AI-assisted labeling unit 6 automatically labels the lesion area based on the deep learning model.

[0035] This data automatic collection and standardized processing platform based on multimodal ophthalmic equipment, the AI-assisted labeling unit 6 can automatically mark the diseased area based on the U-Net model, thereby improving processing efficiency.

[0036] To sum up, when the data automatic acquisition and standardization processing platform based on multimodal ophthalmic equipment is in use, the multimodal ophthalmic equipment will first upload the data to the platform in real time through the hardware interface, and then the data will be format converted, preprocessed and labeled through the standardization processing module 11. The processed data is stored in the database and output through a visual interface (such as a visual data dashboard 9) or API, so as to facilitate the diagnosis and treatment of patients. This is the use feature of the data automatic acquisition and standardization processing platform based on multimodal ophthalmic equipment. The content not described in detail in this description belongs to the existing technology known to professional and technical personnel in this field.

[0037] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An automated data acquisition and standardized processing platform based on multimodal ophthalmic equipment, including: The device end (1) is characterized in that: the output end of the device end (1) is connected to an interface protocol converter (2); The output end of the interface protocol converter (2) is connected to an automatic trigger acquisition unit (3), the output end of the automatic trigger acquisition unit (3) is connected to a format conversion unit (4) for converting a format, the output end of the format conversion unit (4) is connected to a data preprocessing unit (5) for preprocessing data, and the output end of the data preprocessing unit (5) is connected to an AI-assisted annotation unit (6).

2. The data automatic acquisition and standardization processing platform based on multimodal ophthalmic equipment according to claim 1 is characterized by: The output end of the AI-assisted annotation unit (6) is connected to a distributed database (7), and the output end of the distributed database (7) is respectively connected to a RESTful API interface (8) and a visual data dashboard (9).

3. The data automatic acquisition and standardization processing platform based on multimodal ophthalmic equipment according to claim 1 is characterized by: The device end (1) includes a slit lamp (101), a biometer (102), a computer ophthalmometer (103), a tonometer (104), a comprehensive ophthalmometer (105), a corneal topographer (106), a fundus camera (107) and a corneal endothelial cell counter (108).

4. The automatic data acquisition and standardization processing platform based on multimodal ophthalmic equipment according to claim 1 is characterized by: The device end (1) and the interface protocol converter (2) both belong to the hardware module (10).

5. The data automatic acquisition and standardization processing platform based on multimodal ophthalmic equipment according to claim 1 is characterized by: The automatic triggering acquisition unit (3) comprises a structured text data acquisition unit (301), an image data acquisition unit (302), a video data acquisition unit (303) and a text report acquisition unit (304).

6. The platform for automatic data acquisition and standardization processing based on multimodal ophthalmic equipment according to claim 1, characterized in that: The data pre-processing unit (5) includes a denoising processing unit (501), a normalization processing unit (502) and a registration processing unit (503).

7. The data automatic acquisition and standardization processing platform based on multimodal ophthalmic equipment according to claim 1 is characterized by: The automatic triggering acquisition unit (3), the format conversion unit (4), the data pre-processing unit (5) and the AI-assisted annotation unit (6) all belong to the standardization processing module (11).

8. The data automatic acquisition and standardization processing platform based on multimodal ophthalmic equipment according to claim 2 is characterized by: The distributed database (7), RESTful API interface (8) and visual data dashboard (9) all belong to the storage and application module (12).

9. The data automatic acquisition and standardization processing platform based on multimodal ophthalmic equipment according to claim 1 is characterized by: The interface protocol converter (2) includes multiple communication interfaces such as DICOM, HL7, RS232, HTTPS, etc.

10. The data automatic acquisition and standardization processing platform based on multimodal ophthalmic equipment according to claim 1 is characterized by: The AI-assisted labeling unit (6) automatically labels the lesion area mainly based on a deep learning model.

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