WO2020118535A1

WO2020118535A1 - B-mode ultrasound intelligent auxiliary acquisition method and system

Info

Publication number: WO2020118535A1
Application number: PCT/CN2018/120396
Authority: WO
Inventors: 林江峰
Original assignee: 广东医动科技有限公司
Priority date: 2018-12-11
Filing date: 2018-12-11
Publication date: 2020-06-18
Also published as: CN113556978A

Abstract

Disclosed by the present invention is a B-mode ultrasound intelligent auxiliary acquisition method and system, specifically: a medical imaging standard database comprising valid image data is first configured; then a detection data stream is acquired and a detection imaging data stream is then divided into image frames; the image frames are compared to the valid image data; when the comparison result is that same are similar, an image frame from the current moment and detection imaging data streams within time periods before and after the image frame are automatically obtained as the detection result; when the diagnosis is that same are not similar, the acquisition of detection imaging data streams and image frames is manually controlled, which is then used as a detection result. The B-mode ultrasound intelligent auxiliary acquisition method and system provided by the present invention may reduce the requirements for the specialized skill of inspection staff when performing B-mode ultrasonic inspection; in most cases, a detection result may be obtained automatically, and thus the technical problem in the existing technology in which only specialized technicians may operate B-mode ultrasound is overcome, and the application range of B-mode ultrasound is expanded.

Description

Method and system for B-super intelligent auxiliary collection

Technical field

The present invention relates to the field of medical equipment, and in particular, to a B-ultrasonic intelligent auxiliary collection method and system.

Background technique

B-ultrasound detection is the most direct and accurate detection method for monitoring the internal organs and blood flow information of the human body. Existing B-ultrasound equipment requires professional technicians with professional medical knowledge and detection skills to operate the human body. It is necessary to make a comprehensive judgment based on the placement, angle, and displayed image of the detection head to determine the detection image to be acquired as the detection conclusion.

Due to the above reasons, there is currently a serious shortage of testing technicians. It is impossible for primary medical institutions such as primary hospitals and remote health centers, clinics and other primary medical institutions to also be equipped with testing technicians, so it will be impossible to perform B-ultrasonic testing in primary medical institutions. Patients with corresponding testing needs may not be tested in time and may delay diagnosis and treatment.

Summary of the invention

The purpose of the present invention is to provide a B-ultrasound intelligent auxiliary collection method, which aims to solve the technical problems that the existing B-ultrasound can only be operated with the help of professional technicians, thus most of the basic medical institutions cannot perform corresponding detection services.

The invention provides a B-mode intelligent auxiliary collection method.

The collection method includes:

Step 1: Determine the medical imaging standard database, which includes various effective image data formed after B-ultrasound corresponding to various parts, organs and diseases of the human body, and marks are set on the effective image data ;

Step 2: After selecting body parts, organs and diseases, use B-mode imaging equipment to detect the human body to form a detection image data stream;

Step 3: Divide the detected image data stream into multiple image frames, compare each image frame with the corresponding multiple effective image data, determine the similarity, and output the comparison result;

Step 4: When the comparison result is similar, obtain the image frame and save it, or obtain and save the inspection image data stream in the time period before and after the image frame to save the image frame or the inspection image The data stream is used as the detection result; when the comparison result is not similar, go to step 5;

Step 5: The operator continuously uses the B-mode imaging device to detect the human body, and manually controls the B-mode imaging device to acquire the inspection image data stream or a part of the inspection images constituting the inspection image data stream, using the manually acquired inspection The image data stream or inspection image is used as the inspection result to complete the acquisition.

The B-mode intelligent auxiliary acquisition method disclosed in the present invention first sets up a medical imaging standard database with effective image data, and then uses the B-mode imaging equipment to obtain the detection image data stream of the organ, and at the same time, the detection image data stream and the pre-stored effective image Data comparison. If the comparison is similar, the acquired detection image data stream and the image frame in the data stream at that moment are considered as the detection result, and the part of the detection image data stream and image frame are automatically used as the detection result; if the comparison is not similar, The detection personnel can manually intercept the corresponding detection image data stream and image frame as the detection result. This method enables only the trained personnel to operate the B-mode ultrasound equipment to automatically obtain the test results based on the comparison results, or to manually detect when the test conclusion fails to be obtained, thereby overcoming the prior art, only professional technicians can operate the B Ultra technical problems have expanded the application range of B-ultrasound detection.

The invention also discloses a B-mode intelligent auxiliary collection system.

The system includes:

A remote server, which stores a medical imaging standard database, which includes a variety of effective image data that have been formed after B-ultrasound corresponding to various parts of the human body, organs, and diseases. Marks are set on the image data;

A host, the host is connected to the B-mode imaging device, receives the detected image data stream, and communicates with the remote server;

B-mode imaging device, the B-mode imaging device is used to detect the human body, forming a detection image data stream;

The host includes a key module, a control module, a data processing module, a communication module, and a cache module. The key module and the communication module are connected to the control module, and the control module is based on the Human body parts, organs and diseases, control and receive the detected image data stream detected by the B-mode imaging device and store them in the cache module, the control module controls the communication module to obtain the data from the remote server Valid image data, and send the acquired valid image data to the data processing module; the data processing module divides the detected image data stream into a plurality of image frames according to the valid image data, compares and judges The similarity between the image frame and the effective image data;

When determining that the image frame and the effective image data are similar, the data processing module outputs a similar image frame to the control module; the control module sends a control instruction to the cache module according to the comparison result, so that The cache module uses the cached image frame or the detected image data stream in the time period before and after the image frame as a detection result;

When the data processing module determines that the image frame is not similar to the effective image data, the key module sends a data entry instruction to the control module under artificial control, and the control module thereby controls the cache module to The detection image at the moment when the key module is pressed or the detection image data stream in the time period before and after the detection image as a detection result;

A medical diagnosis system that receives the detection result through the communication module and makes an artificial diagnosis based on the detection result.

The B-mode intelligent auxiliary acquisition system disclosed in the present invention stores the medical image standard database with effective image data on a remote server, and obtains the detected image data stream of the human body through the B-mode imaging device, and sends it to the host. The data processing module in the host computer can directly obtain valid image data from the remote server according to the received detected image data stream, and make a comparison conclusion between the image frames in the detected image data stream and the effective image data. When the comparison is similar, the host directly determines that the detected image data stream and part of the image frames in the data stream are the detection results; when the comparison result is not similar, you can directly obtain the key press detection by the control of the key module The detected image data stream in the time period before and after the image or the detected image is used as the detection result. The B-mode intelligent auxiliary acquisition method disclosed by the present invention can minimize the requirements for professional technicians in the process of B-mode ultrasound detection, and can enable anyone who has undergone inspection training to operate the B-mode ultrasound equipment to expand the scope of B-mode ultrasound detection , Overcoming the technical problems in the existing technology, only professional technicians can operate B-mode ultrasound, expanding the application scope of B-mode ultrasound detection.

BRIEF DESCRIPTION

FIG. 1 is a timing diagram of the B-super intelligent auxiliary collection method of the present invention;

2 is a schematic flowchart of the B-super intelligent auxiliary collection method of the present invention;

3 to 5 are schematic diagrams of modules of the B-super intelligent auxiliary acquisition system of the present invention;

6 is a software operation interface of the B-super intelligent auxiliary acquisition system of the present invention.

detailed description

The present invention is further elaborated and explained below in conjunction with specific embodiments and the accompanying drawings of the specification:

Please refer to FIG. 1 and FIG. 2, the present invention discloses a B-mode intelligent auxiliary acquisition method, the method includes the following steps:

Step 1: Determine the medical imaging standard database, which includes various effective image data formed after B-ultrasound corresponding to various parts, organs and diseases of the human body, and marks are set on the effective image data .

Effective image data refers to a B-mode ultrasound image that can clearly indicate the image, position, blood flow information, size and other information of the corresponding human body parts and organs after detection, and the corresponding mark is made on the B-mode ultrasound image to distinguish For other normal B-mode ultrasound images. Marking includes: at least one of a plurality of marking points, a plurality of marking areas, and a plurality of marking parameters, wherein the marking points mark the location of the lesion or abnormality; the marking area marks the range where the lesion or abnormality is located, or the criticality where different organs are located Boundary, etc.; multiple marking parameters mark the abnormal areas and ranges of various medical parameters detected by ultrasound. In this method, abnormalities and diseases in B-mode ultrasound images can be determined based on the content of the mark.

Among them, the medical imaging standard database is formed by classifying and storing the above-mentioned effective image data according to the human body parts, organs and corresponding disease types or names to be detected, and based on the human body parts, organs and corresponding disease types and names. index.

Similarity calculation parameters, mathematical calculation methods, and similarity judgment thresholds of marked points, marked areas, or marked parameters in effective image data of different body parts, organs, and corresponding disease types and names are not completely the same.

Specifically, the formation of a medical imaging standard database includes the following methods:

Step 11: Use the B-mode ultrasound device to detect the human body to form the detected image data stream;

Step 12: Manually determine the human body parts, organs and corresponding disease types or names corresponding to the detection content in the detection image data stream;

Among them, the determination of the detected image data stream in this step requires professional physicians or technicians to operate, and after determining the corresponding body parts, organs, and types and names of diseases, the location of lesions or abnormalities can be marked.

Step 13: Divide the detected image data stream into multiple image pictures, and select at least one image picture that best describes the human body part, organ, and disease type and name from the multiple image pictures as effective image data.

Step 14: Set a mark on the effective image data, the mark including at least one of a plurality of mark points, a plurality of mark areas, or a plurality of mark parameters.

Step 15: Set the attributes of the effective image data, the attributes are the corresponding human body parts, organs and corresponding disease types and names, and then according to the set attributes, all valid image data containing marked points, marked areas or marked parameters Save to form a medical imaging standard database.

Step 2: After selecting human body parts, organs and diseases, use the B-mode imaging device 30 to detect the human body to form a detection image data stream.

In this step, the human body parts, organs and diseases to be detected need to be selected before detection, which is beneficial to select the corresponding effective image data from the medical imaging standard database as a reference and quickly compare abnormalities. After selecting the human body parts, organs, and diseases, the B-mode imaging device 30 collects the detection image data stream at the corresponding position of the human body and transmits the detection image data stream in real time, but it is not directly used as the detection result.

Step 3: Divide the detected image data stream into multiple image frames, compare each image frame with the corresponding multiple effective image data, determine the similarity, and output the comparison result.

It should be noted that the comparison result is similar means that the image frame is compared with multiple valid image data, and the similarity will be formed when the comparison is made. When the value of the similarity meets the medical judgment is similar to each other or meets the judgment standard value When it is determined that they are similar to each other. Specifically, the size of the standard value that meets the similarity of medical judgment may be different according to different medical judgment standards, or a specific doctor may set a specific value.

The method for comparing the image frames of the detected image data stream and the effective image data and determining the results of the comparison include:

Step 31: Set the similarity calculation parameter, mathematical calculation method, and similarity judgment threshold of the marker on each effective image data in advance. Among them, the similarity calculation parameters, mathematical calculation methods, and similarity judgment threshold settings come from the data requirements of different human body parts, organs, and disease types. These contents can be estimated by mathematical estimation methods based on a large number of basic data. These parameters ensure the subsequent continuous calculation. Among them, the similarity judgment threshold, similarity calculation parameters, and mathematical calculation methods are not completely the same in different parts, organs, and diseases.

Step 32: Select effective image data of priority comparison and general comparison from the effective image data. Among them, the distinction between the effective image data of the priority comparison and the general comparison can save the time of the comparison process, and obtain the comparison result quickly and maximumly. Specifically, the selection method includes:

The effective image data for priority comparison is the same data as those of the human body parts, organs, and diseases in the effective image data corresponding to the body parts, organs, and diseases selected before the ultrasound imaging device 30 detects the human body; the general ratio The effective image data of the pair is data in which the human body parts, organs and disease attributes in the effective image data are different from those of the human body parts, organs and diseases selected before the ultrasound imaging apparatus 30 detects the human body.

Step 33: Divide the detected image data stream into multiple image frames.

Step 34: Use the mathematical calculation method and mathematical calculation parameters to calculate the similarity between the multiple image frames and all the effective comparison image data to form a calculation result, and compare the calculation result with the similarity judgment threshold; when the calculation result When it is not less than the similarity judgment threshold, it is judged as similar; when the calculation result is less than the similarity judgment threshold, it is judged as not similar.

Step 35: When it is judged as not similar in step 34, the mathematical calculation method and mathematical calculation parameters are used to calculate the similarity between the multiple image frames and the generally valid priority effective image database to form a calculation result, and the calculation result is similar to Compare the degree judgment threshold; when the calculation result is not less than the similarity judgment threshold, judge it as similar; when the calculation result is less than the similarity judgment threshold, judge as dissimilar, and execute step 5.

Step 5: The operator continuously uses the B-mode imaging device 30 to detect the human body, and manually controls the B-mode imaging device 30 to acquire the inspection image data stream or a part of the inspection images constituting the inspection image data stream, using the manual acquisition The inspection image data stream or inspection image is used as the inspection result to complete the collection.

In this step, only after the comparison does not have similarity, that is to say, the detection result cannot be directly obtained automatically through the comparison, then manually control the operation of acquiring the inspection image data stream and the inspection image, and use the manually acquired inspection image The data stream and the detection image as the detection result are the same as the existing B-ultrasound detection operation. This situation is mainly due to the fact that the effective image data stored in the medical imaging standard database is not comprehensive and cannot reflect and compare all human parts, organs and diseases. At this time, in order to further improve the medical imaging standard database, the method further includes step 6: after manually completing the collection of the inspection image data stream or the inspection image, directly perform artificial diagnosis on the inspection image data stream or the inspection image Distinguish and set the attributes and marks of the detected image data stream or the detected image including human parts, organs, diseases, etc. according to the results of the diagnostic discrimination, and form new effective image data, and convert the new effective image according to the attributes The data is supplemented to the medical imaging standard database to complete the updating of the medical imaging standard database.

After the detection image data stream is manually detected, a professional doctor makes artificial judgment on the detection image data stream and part of the detection images in the data stream, and also marks the body parts, organs, and diseases to form new effective image data . It can be predicted that when this method is used to perform B-ultrasound detection on the human body, when more human specimen data is detected, the more effective image data in the medical imaging standard database is, the more comprehensive it is. When the effective image data is included in all B-ultrasound detection schemes, when this method is used for B-ultrasound detection, it can automatically identify the detection images and detection image data streams in B-ultrasound, so as to directly obtain the detection results, and no longer Need human operation and judgment.

Referring to FIGS. 3 to 5, the present invention also provides a B-mode intelligent auxiliary acquisition system, which includes:

A remote server 10, on which a database of medical imaging standards is stored. The database of medical imaging standards includes various effective image data that have been formed after B-ultrasound corresponding to various parts of the human body, organs, and diseases. A mark is set on the effective image data.

The markers further set on the effective image data include: at least one of a plurality of marking points, a plurality of marking areas, or a plurality of marking parameters; each of the effective graphic data is also provided with a similarity calculation parameter and mathematics of the marking The calculation method and the similarity judgment threshold; the medical imaging standard database is based on the attribute classification and storage of the effective image data of the human body parts, organs and corresponding disease types and names.

A host 20, which is connected to the B-mode imaging device 30, receives the detected image data stream, and communicates with the remote server 10;

B-mode imaging device 30, the B-mode imaging device 30 is used to detect the human body and form a detected image data stream;

The host 20 includes a key module 210, a control module 220, a data processing module 230, a communication module 240, and a cache module 250. The key module 210 and the communication module 240 are connected to the control module 220 and the control module 220 Control and receive the detected image data stream detected by the B-mode imaging device 30 according to the body parts, organs and diseases to be detected entered by the key module 210 and store them in the buffer module 250, the control module 220 Controlling the communication module 240 to acquire the effective image data from the remote server 10, and send the acquired effective image data to the data processing module 230; the data processing module 230 is based on the effective image data Divide the detected image data stream into multiple image frames and compare them, and determine the similarity between the image frames and the effective image data;

The data processing module 230 outputs a similar image frame to the control module 220 when determining that the image frame and the effective image data are similar; the control module 220 sends a control instruction to the cache module according to the comparison result 250, causing the cache module 250 to use the cached image frame or the detected image data stream in the time period before and after the image frame as a detection result;

When the data processing module 230 determines that the image frame and the effective image data are not similar, the key module 210 sends a data entry instruction to the control module 220 under artificial control, and the control module 220 thereby controls the The cache module 250 uses the detection image at the moment when the key module 210 is pressed or the detection image data stream in the time period before and after the detection image as the detection result;

A medical diagnosis system 40. The medical diagnosis system 40 receives the detection result through the communication module 240 and makes an artificial diagnosis according to the detection result.

The doctor obtains the test result from the medical test system and makes a diagnosis based on the test result; when the test result is obtained by pressing the human control by pressing the key module 210, the test image and the test image of the test result by the doctor The data stream sets attributes including human body parts, organs, diseases, and markers, and forms new effective image data, and supplements the new effective image data to the medical imaging standard database according to the attributes, thereby completing the update of the medical imaging standard database.

The control module 220 includes a judgment selection module 221. The judgment selection module 221 sends a query and a retrieval command to the remote server 10 according to the body parts, organs, and diseases to be detected entered by the key module 210, from the remote The server 10 preferentially retrieves the effective image data having the same body parts, organs and disease attributes as the priority effective image data, and sends the preferential effective image data to the data processing module 230; then it is transferred from the remote server 10 The effective image data that does not have the same body parts, organs, and disease attributes is taken as general effective image data, and the general effective image data is sent to the data processing module 230.

The data processing module 230 includes:

A dividing module 231, the dividing module 231 is used to divide the detected image data stream stored in the buffer module 250 into a plurality of image frames;

The calculation module 232, based on the priority effective image data or the general effective image data, the multiple image frames divided by the dividing module 231, according to the pre-set mark points, mark areas or mark parameters on each effective image data Similarity calculation parameters and mathematical calculation methods sequentially calculate the similarity between the image frame and the priority effective image data or general effective image data;

A comparison module 233, the comparison module 233 determines whether the image frame is similar to the effective priority effective image data or general effective image data according to the similarity and a preset similarity judgment threshold, and outputs the judgment result to Control module 220;

The control module 220 obtains the corresponding detection result from the cache module 250 according to the judgment result, and sends the detection result to the remote server 10 via the communication module 240.

With reference to FIG. 6, in the system of the present invention, effective graphic data having at least one of a plurality of marking points, a plurality of marking areas, or a plurality of marking parameters, each effective image data is also provided with a similarity calculation of the marking Parameters, mathematical calculation methods and similarity judgment threshold; multiple effective image data are classified and stored according to the attributes of human parts, organs and corresponding disease types and names to form a medical imaging standard database, and the medical imaging standard database is stored in a remote In the server 10; in operation, first the B-mode imaging device 30 acquires the detected image data stream, and divides the detected image data stream into a plurality of image frames, sends the image frames to the host 20, using the data processing module 230 in the host 20 Compare the image frame and the effective image data to complete the comparison result. When the comparison is similar, the control module 220 automatically saves the image frame and the detected image data stream in the time period before and after the image frame, and sends it to the communication module 240, and the communication module 240 sends it to the medical diagnosis system 40. The diagnosis system 40 makes a corresponding diagnosis and treatment conclusion. When the comparison is not similar, under the artificial control, the key module 210 sends a data entry instruction to the control module 220, and the control module 220 controls the cache module 250 to detect the image or the time period before and after the image The detected image data stream is used as the detection result. The detection result is sent to the medical diagnosis system 40. The doctor obtains the test result from the medical test system and makes a diagnosis based on the test result; when the test result is obtained by pressing the human control by pressing the key module 210, the test image and the test image of the test result by the doctor The data stream sets attributes including human body parts, organs, diseases, and markers, and forms new effective image data, and supplements the new effective image data to the medical imaging standard database according to the attributes, thereby completing the update of the medical imaging standard database.

Similarly, the effective image data in the medical imaging standard database is also formed by artificially marking the detection images intercepted in the detection data stream, filling in attributes, setting similarity calculation parameters and similarity calculation methods. It can also be a medical imaging standard database that is expanded after learning a lot of marked effective graphics data through artificial intelligence.

Similarly, the marked points, marked areas, marked parameters, similarity calculation parameters, and similarity calculation methods of an organ can be learned through artificial intelligence.

In this embodiment, as long as the positions of the corresponding human organs and parts initially marked manually are accurate; as long as the marked points, marked areas, marked parameters and similarity calculation parameters and similarity calculation methods of the effective image data initially marked manually Accurately, after enough artificial intelligence learning of the entered data, the human body image model and medical standard database can sufficiently cover all the human body data and the B-ultrasound data corresponding to the human body.

Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention, rather than limiting the protection scope of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand The technical solutions of the present invention can be modified or equivalently replaced without departing from the essence and scope of the technical solutions of the present invention.

Claims

A B-mode intelligent auxiliary collection method, characterized in that it includes the following steps:

Step 1: Determine the medical imaging standard database, which includes various effective image data formed after B-ultrasound corresponding to various parts, organs and diseases of the human body, and marks are set on the effective image data ;

Step 2: After selecting body parts, organs and diseases, use B-mode imaging equipment to detect the human body to form a detection image data stream;

Step 3: Divide the detected image data stream into multiple image frames, compare each image frame with the corresponding multiple effective image data, determine the similarity, and output the comparison result;

Step 4: When the comparison result is similar, obtain the image frame and save it, or obtain and save the inspection image data stream in the time period before and after the image frame to save the image frame or the inspection image The data stream is used as the detection result; when the comparison result is not similar, go to step 5;

Step 5: The operator continuously uses the B-mode imaging device to detect the human body, and manually controls the B-mode imaging device to acquire the inspection image data stream or a part of the inspection images constituting the inspection image data stream, using the manually acquired inspection The image data stream or inspection image is used as the inspection result to complete the acquisition.
The B-mode intelligent auxiliary collection method according to claim 1, wherein the method further comprises:

Step 6: After manually completing the inspection image data stream or inspection image acquisition, directly perform artificial diagnosis and discrimination on the inspection image data stream or the inspection image, and set the inspection image data stream or location based on the result of the diagnostic discrimination The detection image includes attributes and marks of human body parts, organs, and diseases, and forms new effective image data. The new effective image data is added to the medical imaging standard database according to the attributes, thereby completing the update of the medical imaging standard database.
The B-mode intelligent auxiliary acquisition method according to claim 1 or 2, wherein the method for determining the medical imaging standard database in step 1 includes the following steps:

Step 11: Use the B-mode ultrasound device to detect the human body to form the detected image data stream;

Step 12: Manually determine the human body parts, organs and corresponding disease types or names corresponding to the detection content in the detection image data stream;

Step 13: Divide the detected image data stream into multiple image pictures, and select at least one image picture that best describes the human body part, organ, disease type and name from the multiple image pictures as valid image data;

Step 14: Set a mark on the effective image data, the mark including at least one of a plurality of marking points, a plurality of marking areas, or a plurality of marking parameters;

Step 15: Set the attributes of the effective image data, the attributes are the corresponding human body parts, organs and corresponding disease types and names, and then according to the set attributes, all valid image data containing marked points, marked areas or marked parameters Save to form a medical imaging standard database.
The B-mode intelligent auxiliary collection method according to claim 3, wherein step 3 includes the following steps:

Step 31: Set in advance similarity calculation parameters, mathematical calculation methods, and similarity judgment thresholds of the marks on each effective image data;

Step 32: Select effective image data of priority comparison and general comparison from the effective image data;

Step 33: Divide the detected image data stream into multiple image frames;

Step 34: Use the mathematical calculation method and mathematical calculation parameters to calculate the similarity between the multiple image frames and all the effective comparison image data to form a calculation result, and compare the calculation result with the similarity judgment threshold; when the calculation result When it is not less than the similarity judgment threshold, it is judged as similar; when the calculation result is less than the similarity judgment threshold, it is judged as not similar.

Step 35: When it is judged as not similar in step 34, the mathematical calculation method and mathematical calculation parameters are used to calculate the similarity between the multiple image frames and the generally valid priority effective image database to form a calculation result, and the calculation result is similar to Compare the degree judgment threshold; when the calculation result is not less than the similarity judgment threshold, judge it as similar; when the calculation result is less than the similarity judgment threshold, judge as dissimilar, and execute step 5.
The B-super intelligent auxiliary collection method according to claim 4, wherein the marked points, marked areas or marked parameters in the effective image data under the different human body parts, organs and corresponding disease types and names Similarity calculation parameters, mathematical calculation methods, and similarity judgment thresholds are not completely the same.
The B-mode intelligent auxiliary acquisition method according to claim 4, wherein the effective image data of the priority comparison are those human body parts, organs and disease attributes in the effective image data and the B-mode imaging device to detect the human body The previously selected human body parts, organs and diseases correspond to the same data; the effective image data of the general comparison are those of the human body parts, organs and disease attributes in the effective image data and the B-mode imaging device before the detection of the human body Data for different parts of the human body, organs and diseases.
A B-mode intelligent auxiliary collection system, characterized in that the system includes:

A remote server, which stores a medical imaging standard database, which includes a variety of effective image data that have been formed after B-ultrasound corresponding to various parts of the human body, organs, and diseases. Marks are set on the image data;

A host, the host is connected to the B-mode imaging device, receives the detected image data stream, and communicates with the remote server;

B-mode imaging device, the B-mode imaging device is used to detect the human body, forming a detection image data stream;

The host includes a key module, a control module, a data processing module, a communication module, and a cache module. The key module and the communication module are connected to the control module, and the control module is based on the Human body parts, organs and diseases, control and receive the detected image data stream detected by the B-mode imaging device and store them in the cache module, the control module controls the communication module to obtain the data from the remote server Valid image data, and send the acquired valid image data to the data processing module; the data processing module divides the detected image data stream into a plurality of image frames according to the valid image data, compares and judges The similarity between the image frame and the effective image data;

When determining that the image frame and the effective image data are similar, the data processing module outputs a similar image frame to the control module; the control module sends a control instruction to the cache module according to the comparison result, so that The cache module uses the cached image frame or the detected image data stream in the time period before and after the image frame as a detection result;

When the data processing module determines that the image frame is not similar to the effective image data, the key module sends a data entry instruction to the control module under artificial control, and the control module thereby controls the cache module to The detection image at the moment when the key module is pressed or the detection image data stream in the time period before and after the detection image as a detection result;

A medical diagnosis system that receives the detection result through the communication module and makes an artificial diagnosis based on the detection result.
The B-super intelligent auxiliary collection system according to claim 7, characterized in that the doctor obtains the detection result from the medical detection system and makes a diagnosis based on the detection result; when the detection result is manually controlled by pressing the button module When obtained, the doctor sets attributes including human body parts, organs, diseases, and markers on the detection image and the detection image data stream of the detection result, and forms new effective image data, and then sets the new effective image data according to the attributes Supplement to the medical imaging standard database to complete the update of the medical imaging standard database.
The B-super intelligent auxiliary acquisition system according to claim 8, wherein the markers further set on the effective image data include: at least one of a plurality of marking points, a plurality of marking areas, or a plurality of marking parameters; each The effective graphic data is also provided with marked similarity calculation parameters, mathematical calculation methods and similarity judgment thresholds; the medical imaging standard database is an attribute for the effective image data of the human body parts, organs and corresponding disease types and names Classification preservation is formed.
The B-super intelligent auxiliary collection system according to claim 9, characterized in that the control module includes a judgment selection unit, and the judgment selection unit sends an inquiry according to the human body parts, organs and diseases to be detected entered by the key module and Retrieve commands to the remote server, preferentially retrieve effective image data with the same body parts, organs and disease attributes from the remote server as priority effective image data, and send the priority effective image data to the data processing module ; Then retrieve the effective image data from the remote server that do not have the same body parts, organs and disease attributes as general effective image data, and send the general effective image data to the data processing module;

The data processing module includes:

A dividing module, the dividing module is used to divide the detected image data stream stored in the buffer module into a plurality of image frames;

A calculation module, based on the prioritized effective image data or general effective image data, and a plurality of image frames divided by the dividing module, according to the similarity of the marked points, marked areas or marked parameters on each effective image data set in advance Calculation parameters and mathematical calculation methods to sequentially calculate the similarity between the image frame and the priority effective image data or general effective image data;

A comparison module, the comparison module judges whether the image frame is similar to the effective priority effective image data or general effective image data according to the similarity and a preset similarity judgment threshold, and outputs a judgment result to the control module ;

The control module obtains the corresponding detection result from the cache module according to the judgment result, and sends the detection result to the remote server via the communication module.