Medical image analysis system and method based on AR glasses

Abstract

The invention discloses a medical image analysis system and method based on AR glasses, and the system comprises the AR glasses which are used for receiving medical image data and displaying an analysis result; the medical image analysis model is used for automatically analyzing the medical image data, identifying a focus and generating a diagnosis suggestion; the data transmission module is used for transmitting the medical image data from the AR glasses to the medical image analysis model and returning an analysis result to the AR glasses; and the interaction module is used for receiving an instruction of a doctor and adjusting a display mode of an analysis result. The method comprises the following steps: S1, acquiring medical image data; s2, preprocessing the medical image; s3, analyzing the medical image; s4, visualizing an analysis result; s5, a doctor interacts with the system; and S6, recording and sharing diagnosis results. The system has the advantages that the AR glasses and the medical image system can fully interact, the focus is automatically identified by using the deep learning model, the diagnosis suggestion is generated, and the workload of doctors is reduced.

Description

Technical Field

[0001] The present invention relates to the field of intelligent medicine, and specifically to a medical image analysis system and method based on AR glasses. Background Art

[0002] Traditional medical image analysis mainly relies on doctors' experience and manual operations, and there are many problems with this method: 1. Low efficiency: Doctors need to spend a lot of time manually analyzing images, especially in complex cases, and the diagnosis process takes a long time. 2. Strong subjectivity: The diagnosis results are easily affected by doctors' personal experience and subjective judgments, which may lead to misdiagnosis or missed diagnosis; Inconvenient interaction: The traditional image viewing method relies on a computer screen, and doctors cannot view and analyze images in real time during operations or ward rounds. There are also some problems with the existing AR technology applied to the medical field. Because most current AR systems only support the display and simple interaction of images, lack automatic analysis functions, and cannot assist doctors in quickly locating lesions. Moreover, when dealing with large-scale medical image data, existing systems often have delays and cannot meet the needs of real-time diagnosis.

[0003] In view of this, it is necessary to provide a medical image analysis system and method based on AR glasses. Summary of the Invention

[0004] The medical image analysis system and method based on AR glasses provided by the present invention effectively solve the problem that existing AR medical image analysis fails to fully combine AR glasses with image data.

[0005] The technical solution adopted by the present invention is as follows:

[0006] The medical image analysis system based on AR glasses includes:

[0007] AR glasses, which are used to receive medical image data and display analysis results;

[0008] A medical image analysis model, which is used to automatically analyze the medical image data, identify lesions and generate diagnostic suggestions;

[0009] A data transmission module, which is used to transmit the medical image data from the AR glasses to the medical image analysis model and return the analysis results to the AR glasses;

[0010] An interaction module, which is used to receive doctors' instructions and adjust the display mode of the analysis results.

[0011] Furthermore, the medical image analysis model includes:

[0012] An image preprocessing module, which is used to denoise and enhance medical images;

[0013] A lesion recognition module for identifying lesion regions in images through deep learning algorithms;

[0014] A diagnosis suggestion generation module for generating diagnosis suggestions based on the recognition results.

[0015] Furthermore, the AR glasses support gesture control, and doctors can adjust the display position and size of the analysis results through gestures.

[0016] Furthermore, the system also includes a voice recognition module for receiving doctors' voice commands and performing corresponding operations.

[0017] Furthermore, the data transmission module realizes real-time transmission and analysis of medical image data through a 5G network or edge computing nodes.

[0018] A medical image automatic analysis method based on AR glasses includes the following steps:

[0019] S1. Obtain medical image data: The system obtains the patient's medical image data through medical imaging equipment;

[0020] S2. Medical image preprocessing: Denoise and adjust the contrast of the obtained medical images;

[0021] S3. Medical image analysis: Identify lesion regions in the image and put forward diagnosis suggestions for the identified lesions;

[0022] S4. Visualization of analysis results: Display lesion regions and diagnosis suggestion information on the AR glasses;

[0023] S5. Interaction between doctors and the system: Doctors interact with the system through the AR glasses;

[0024] S6. Recording and sharing of diagnosis results: Record and share the analysis results and doctors' diagnosis opinions.

[0025] Furthermore: The medical image data in S1 includes at least one of X-ray films, CT scan images, and MRI images.

[0026] Furthermore: The analysis results in S6 include at least one of lesion localization, lesion classification, and diagnosis suggestions.

[0027] Furthermore: It also includes S7. Feedback and model optimization: Doctors correct incorrect analysis results, the system records the correction data and uses it for model training, and through continuous learning technology, the model can adapt to new cases and image types.

[0028] Furthermore: The lesion regions in S3 are highlighted.

[0029] Advantages of the invention:

[0030] 1. The AR glasses can fully interact with the medical imaging system, automatically identify lesions using a deep learning model, and generate diagnostic suggestions, reducing the workload of doctors.

[0031] 2. The AR glasses can display the analysis results in real time and support natural interaction methods such as gesture control and voice commands, ensuring that doctors obtain the first-hand imaging data of patients.

[0032] 3. The entire system supports the fusion analysis of various imaging data such as CT and MRI, further improving the diagnostic accuracy.

[0033] 3. When analyzing imaging data, the lesions can be highlighted to further improve the recognition rate of lesions. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a flowchart of the method for medical imaging analysis based on AR glasses provided by the embodiments of the present application. DETAILED DESCRIPTION

[0035] In order to make the above objects, features, and advantages of the present invention more obvious and understandable, the following detailed description of the specific embodiments of the present invention will be given with reference to the accompanying drawings.

[0036] The first embodiment provided by the present application is a medical imaging analysis system based on AR glasses, including:

[0037] AR glasses, for receiving medical imaging data and displaying the analysis results;

[0038] A medical imaging analysis model, for automatically analyzing the medical imaging data, identifying lesions, and generating diagnostic suggestions;

[0039] A data transmission module, for transmitting the medical imaging data from the AR glasses to the medical imaging analysis model and returning the analysis results to the AR glasses;

[0040] An interaction module, for receiving the doctor's instructions and adjusting the display mode of the analysis results.

[0041] Specifically, the medical imaging analysis model includes:

[0042] An image preprocessing module, for denoising and enhancing the medical imaging;

[0043] A lesion identification module, for identifying the lesion area in the image through a deep learning algorithm;

[0044] A diagnostic suggestion generation module, for generating diagnostic suggestions according to the identification results.

[0045] In the above design, the medical image analysis system based on AR glasses can automatically analyze images and display the condition, cause of the disease, and diagnostic suggestions to doctors through AR glasses, improving the diagnostic efficiency.

[0046] Specifically, the AR glasses support gesture control, and doctors can adjust the display position and size of the analysis results through gestures.

[0047] In the above design, the position and size of the analysis results are adjusted through gesture control, ensuring that the display results are presented on doctors with different body types, heights, and observation habits.

[0048] Specifically, the system further includes a voice recognition module for receiving doctors' voice commands and performing corresponding operations.

[0049] In the above design, freeing doctors' hands through voice commands can improve the convenience of operation.

[0050] Specifically, the data transmission module realizes the real-time transmission and analysis of medical image data through a 5G network or an edge computing node.

[0051] In the above design, 5G network transmission can ensure the timeliness of information transmission.

[0052] The second embodiment provided by this application is a method for automatic analysis of medical images based on AR glasses, including the following steps:

[0053] S1. Obtain medical image data: The system obtains the medical image data of the patient through medical imaging equipment;

[0054] S2. Preprocess the medical image: Denoise and adjust the contrast of the obtained medical image;

[0055] S3. Analyze the medical image: Identify the lesion area in the image and propose diagnostic suggestions for the identified lesion;

[0056] S4. Visualize the analysis results: Display the lesion area and diagnostic suggestion information on the AR glasses;

[0057] S5. Interaction between doctor and system: The doctor interacts with the system through the AR glasses;

[0058] S6. Record and share the diagnostic results: Record and share the analysis results and the doctor's diagnostic opinions.

[0059] In the above design, the six steps from S1 to S6 gradually realize the automatic analysis of medical images, which can improve the efficiency of medical image analysis.

[0060] Specifically, the medical image data in S1 includes at least one of X-ray films, CT scan images, and MRI images.

[0061] Specifically, the analysis results in S6 include at least one of lesion localization, lesion classification, and diagnostic suggestions.

[0062] Specifically, it further includes S7, feedback and model optimization: The doctor corrects incorrect analysis results, the system records the correction data and uses it for model training. Through continuous learning technology, the model can adapt to new cases and image types.

[0063] Specifically, the lesion area in S3 is highlighted.

[0064] The third embodiment provided by this application is a medical image analysis system based on AR glasses, including: an AR glasses for receiving medical image data and displaying analysis results; a medical image analysis model for automatically analyzing the medical image data, identifying lesions, and generating diagnostic suggestions; a data transmission module for transmitting the medical image data from the AR glasses to the medical image analysis model and returning the analysis results to the AR glasses; an interaction module for receiving the doctor's instructions and adjusting the display mode of the analysis results. The medical image analysis model includes: an image preprocessing module for denoising and enhancing medical images; a lesion recognition module for identifying the lesion area in the image through deep learning algorithms; a diagnostic suggestion generation module for generating diagnostic suggestions based on the recognition results. The AR glasses support gesture control, and the doctor adjusts the display position and size of the analysis results through gestures. The system further includes a voice recognition module for receiving the doctor's voice instructions and performing corresponding operations. The data transmission module realizes real-time transmission and analysis of medical image data through a 5G network or an edge computing node.

[0065] The fourth embodiment provided by this application is a medical image automatic analysis method based on AR glasses, including the following steps: S1. Obtain medical image data: The system obtains the medical image data of the patient through a medical imaging device; S2. Preprocess the medical image: Denoise and adjust the contrast of the obtained medical image; S3. Analyze the medical image: Identify the lesion area in the image and put forward a diagnosis suggestion for the identified lesion; S4. Visualize the analysis result: Display the lesion area and the diagnosis suggestion information on the AR glasses; S5. Interaction between the doctor and the system: The doctor interacts with the system through the AR glasses; S6. Record and share the diagnosis result: Record and share the analysis result and the doctor's diagnosis opinion. S7. Feedback and model optimization: The doctor corrects the incorrect analysis result, and the system records the correction data and uses it for model training. Through continuous learning technology, the model can adapt to new cases and image types. The medical image data in S1 includes at least one of X-ray films, CT scan images, and MRI images. The analysis result in S6 includes at least one of lesion localization, lesion classification, and diagnosis suggestion. The lesion area in S3 is highlighted.

[0066] For further detailed description, it should be understood that the above are only specific embodiments of the present invention and are not used to limit the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A medical image analysis system based on AR glasses, characterized by: include, AR glasses, used to receive medical imaging data and display analysis results; A medical image analysis model, used to automatically analyze the medical image data, identify lesions and generate diagnostic suggestions; A data transmission module, used to transmit the medical image data from the AR glasses to the medical image analysis model, and return the analysis results to the AR glasses; The interactive module is used to receive the doctor's instructions and adjust the display mode of the analysis results.

2. The medical image automatic analysis system based on AR glasses according to claim 1 is characterized in that: The medical image analysis model includes: Image preprocessing module, used for denoising and enhancing medical images; Lesion recognition module, used to identify lesion areas in images through deep learning algorithms; The diagnosis suggestion generation module is used to generate diagnosis suggestions based on the recognition results.

3. The medical image automatic analysis system based on AR glasses according to claim 1, characterized in that: The AR glasses support gesture control, and doctors use gestures to adjust the display position and size of the analysis results.

4. The medical image automatic analysis system based on AR glasses according to claim 1, characterized in that: The system also includes a voice recognition module for receiving a doctor's voice instructions and executing corresponding operations.

5. The medical image automatic analysis system based on AR glasses according to claim 1, characterized in that: The data transmission module realizes real-time transmission and analysis of medical imaging data through 5G network or edge computing nodes.

6. The method for automatic analysis of medical images based on AR glasses is characterized by: The steps include: S1. Obtaining medical imaging data: The system obtains the patient's medical imaging data through medical imaging equipment; S2, medical image preprocessing: denoising and adjusting contrast of acquired medical images; S3. Medical image analysis: Identify the lesion area in the image and make diagnostic suggestions for the identified lesions; S4. Visualization of analysis results: displaying the lesion area and diagnostic suggestion information on AR glasses; S5, Doctor-system interaction: Doctors interact with the system through AR glasses; S6. Recording and sharing of diagnostic results: Record and share analysis results and doctors’ diagnostic opinions.

7. The method for automatic analysis of medical images based on AR glasses according to claim 6, characterized in that: The medical imaging data in S1 includes at least one of X-rays, CT scan images, and MRI images.

8. The method for automatic analysis of medical images based on AR glasses according to claim 6, characterized in that: The analysis result in S6 includes at least one of lesion localization, lesion classification, and diagnosis suggestion.

9. The method for automatic analysis of medical images based on AR glasses according to claim 6, characterized in that: It also includes S7, feedback and model optimization: doctors correct incorrect analysis results, the system records the correction data and uses it for model training. Through continuous learning technology, the model can adapt to new cases and image types.

10. The method for automatic analysis of medical images based on AR glasses according to claim 6, characterized in that: The lesion area in S3 is highlighted.

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