CN112863647A - Video stream processing and displaying method, system and storage medium - Google Patents
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Abstract
The invention discloses a video stream processing and displaying method, a system, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence, wherein the method comprises the steps of processing an original video stream to obtain a frame-extracted image and a frame-not-extracted image; inputting the frame-extracted image into an ai model to obtain a first image with detected and segmented coordinate points and a classification result; encoding the non-decimated image and the first image into a target video stream; and the target video stream is pushed to a client side for display through rtsp, so that the accuracy of analyzing the image by a doctor is improved, and the real-time property of the acquired image is ensured.
Description
Technical Field
The present invention relates to the field of artificial intelligence technologies, and in particular, to a method and a system for processing and displaying a video stream, an electronic device, and a storage medium.
Background
Dicom (digital Imaging and Communications in medicine), which is an international standard for medical images and related information, is an international standard for medical Imaging and Communications. It defines a medical image format that can be used for data exchange with a quality that meets clinical needs.
DICOM image file content consists of two parts: a Header (Header) and picture point Data (Pixel Data) of the parameter information are packaged. Each DICOM file must include the file header. The header begins with the file preamble, which consists of 128 bytes 00H, followed by the DICOM prefix, which is a 4-byte string "DICM" that can be used to determine whether a file is a DICOM file. The header also includes other useful information such as the transmission format of the file, the application that generated the file, etc. The image pixel describes the luminance value of each point of the image. DICOM contains 4 content levels: patient; study (check); series (Series); image (Image).
At present, the mode of acquiring the video stream of the ultrasonic equipment by a video acquisition card can meet the requirements of a dynamic mode and a static mode. But face the following problems:
1. the current dynamic video ai identification result is consistent with the static image ai identification result, but the static jpg image re-identification result is inconsistent;
the doctor's workflow is to search for suspicious positions through dynamic video streams and then to perform further focus judgment on static pictures. The ai on the dynamic video can identify the frame-drawing image in real time, the identification result is drawn on the picture in real time, and a doctor intercepts an image from the real-time video stream at the moment, so that the problem that the image identification result is inconsistent with the dynamic video identification result exists. The system decodes the video stream into pictures, frames, ai predicts the images of the frames. The decimated image is the original uncompressed rgb pixel data. The dynamic video stream and the static picture have the same source, the ai prediction result is the same, and the generated detected and segmented coordinate points are the same, so that the positions marked on the current dynamic video frame-drawing image and the static image are the same, the current dynamic video frame-drawing image and the current static image are stored into a static jpg image, and the static jpg image is sent to the client side to display the picture and the position of the nodule. The image and ai results displayed by the client at this point are correct and the same as the ai results in the dynamic video. However, jpg is lossy compressed, the original pixel value cannot be restored, the decompressed value is different from the original image in the memory, and the jpg image is imported again, so that the ai identification result is different. The doctor may review the patient or may develop a later study and review the previously saved images again, with the ai identification result being different from the previous identification result. The above results in unstable products, which brings troubles to doctors, even misleads the doctors, and causes medical accidents.
2. The cost is high, and the cost is high due to the two main machines;
3. the volume is large, the ultrasonic department is compact, and the two devices usually occupy larger space;
4. and (3) network delay, data are transmitted and received between the two hosts through respective network cards, and the processing flow is more.
Disclosure of Invention
The invention aims to provide a video stream processing and displaying method, a video stream processing and displaying system, electronic equipment and a storage medium, which are used for assisting a doctor in diagnosis, improving the accuracy of image analysis of the doctor and simultaneously ensuring the real-time performance of an acquired image.
In a first aspect, an embodiment of the present invention provides a video stream processing and displaying method, for assisting a doctor to diagnose, including the following steps:
processing an original video stream to obtain a frame extraction image and a frame extraction-free image;
inputting the frame-extracted image into an ai model to obtain a first image with detected and segmented coordinate points and a classification result;
encoding the non-decimated image and the first image into a target video stream;
and pushing the target video stream to a client for displaying through an rtsp.
Optionally, inputting the frame-extracted image into an ai model, and obtaining a first image with the detected and segmented coordinate points and the classification result includes:
inputting the frame-extracted image into an ai model to classify, detect and segment the focus;
and drawing the detected and segmented coordinate points and the classification result on the frame-drawing image to obtain a first image.
Optionally, the image processing and displaying method further includes saving the frame extraction image, and simultaneously saving the frame extraction image as a static png picture.
Optionally, the image processing and displaying method further includes:
inputting the static png picture into an ai model to obtain a second image with detected and segmented coordinate points and a classification result;
and sending the static png picture and the second image to a client side for display through an http protocol.
In a second aspect, an embodiment of the present invention provides a video stream processing display system, where the image processing display system includes:
an ultrasound device connected to the video acquisition device by a video line;
the ultrasonic device comprises a linux ultrasonic ai host, wherein the ultrasonic ai host is provided with a video acquisition device, and the video acquisition device is used for acquiring dynamic video streams of the ultrasonic equipment;
and the linux ultrasonic ai host captures a trigger event, stores a frame extraction image in the memory and locally stores a static png picture at the same time.
In a third aspect, an embodiment of the present invention provides a video stream processing display apparatus, where the apparatus includes:
the first image acquisition module is used for inputting the frame-extracted image of the original video stream into the ai model to obtain a first image with detected and segmented coordinate points and classification results;
the target video stream acquisition module is used for encoding the frame-not-extracted image and the first image of the original video stream into a target video stream;
and the first pushing module is used for pushing the target video stream to the client side for displaying through rtsp.
Optionally, the apparatus further comprises:
and the storage module is used for storing the frame extraction image and simultaneously storing the frame extraction image as a static png picture.
Optionally, the video stream processing and displaying apparatus further includes:
the second image acquisition module is used for inputting the static png picture into an ai model to obtain a second image with detected and segmented coordinate points and classification results;
and the second pushing module is used for sending the static png picture and the second image to a client side for displaying through an http protocol.
In a fourth aspect, the present invention provides an electronic device, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor implements the above method by executing the executable instructions.
In a fifth aspect, the present invention provides a computer readable storage medium having stored thereon computer instructions which, when executed by a processor, implement the steps of the above-described method.
Advantageous effects
The invention provides a video stream processing and displaying method, which comprises the steps of processing an original video stream to obtain a frame extraction image and a frame non-extraction image; inputting the frame-extracted image into an ai model to obtain a first image with detected and segmented coordinate points and a classification result; encoding the non-decimated image and the first image into a target video stream; and the target video stream is pushed to a client side for display through rtsp, so that the accuracy of analyzing the image by a doctor is improved, and the real-time property of the acquired image is ensured.
Drawings
Fig. 1 is a flowchart of a video stream processing and displaying method according to an embodiment of the present invention;
FIG. 2 is a flow chart of a video stream processing and displaying method according to another embodiment of the invention;
FIG. 3 is a block diagram of a video stream processing display system according to an embodiment of the present invention;
FIG. 4 is a block diagram of a video stream processing display device according to an embodiment of the present invention;
FIG. 5 is a block diagram of a video stream processing display device according to another embodiment of the present invention;
fig. 6 is a block diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", may explicitly or implicitly include one or more of the described features. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
In the related art, the sonographer workflow is:
the probe is moved at the scanning position by the operation doctor to carry out real-time dynamic imaging examination, when the probe scans a suspicious position, the image is frozen, the image is carefully observed, a diagnosis suggestion is given, and the diagnosis suggestion is written into a diagnosis report by a reporting doctor. That is, the sonographer must observe both dynamic video streaming images and still pictorial images. At present, artificial intelligence technology in the field of image recognition is based on image pixel processing. Common images such as bmp, jpg, png, etc. are stored with R, G, B three bytes per pixel. An image with 1920 × 1080 resolution consists of 1920 × 1080 pixels, and totally consists of 1920 × 1080 × 3 bytes, and each byte consists of 8 bits, that is, RGB values range from 0 to 255. If only one of 1920 × 1080 × 3 × 8 bits is different, the two images are different, and ai is considered to be two images, the pixel values are different, and the prediction result is likely to be different, but no difference is observed with the naked human eye. In order to save storage space, a common image saving format is jpg, jpg is lossy compression, the compression rate is high, and pictures are very small, such as 1920 × 1080 resolution pictures, bmp saving requires 1920 × 1080 × 3/1024/1024 — 5.93MB, and jpg only needs about 500K, which is close to 1/12. Both disk storage and network transmission are advantageous. It is common to save pictures in the Jpg format.
The invention will be further described with reference to the following description and specific examples, taken in conjunction with the accompanying drawings:
the invention aims to provide a video stream processing and displaying method which is used for assisting a doctor to diagnose, facilitating the doctor to acquire images and ensuring the real-time performance of the acquired images.
Fig. 1 shows a flow chart of a video stream processing display method according to an embodiment of the invention; as shown in fig. 1, the video stream processing and displaying method is used for assisting diagnosis of doctors and comprises the following steps:
s20, processing the original video stream to obtain a frame extraction image and a frame extraction-free image;
s40, inputting the frame-extracted image into an ai model to obtain a first image with detected and segmented coordinate points and a classification result;
s60, encoding the non-frame-extracted image and the first image into a target video stream;
and S80, pushing the target video stream to the client through rtsp for displaying.
The embodiment provides a video stream processing and displaying method, which comprises the steps of processing an original video stream to obtain a frame extraction image and a frame non-extraction image; inputting the frame-extracted image into an ai model to obtain a first image with detected and segmented coordinate points and a classification result; encoding the non-decimated image and the first image into a target video stream; and the target video stream is pushed to a client side for display through rtsp, so that the accuracy of analyzing the image by a doctor is improved, and the real-time property of the acquired image is ensured.
Specifically, inputting the frame-extracted image into an ai model, and obtaining a first image with detected and segmented coordinate points and a classification result includes:
inputting the frame-extracted image into an ai model to classify, detect and segment the focus;
and drawing the detected and segmented coordinate points and the classification result on the frame-drawing image to obtain a first image.
In the related art, the sonographer workflow is:
the probe is moved at the scanning position by the operation doctor to carry out real-time dynamic imaging examination, when the probe scans a suspicious position, the image is frozen, the image is carefully observed, a diagnosis suggestion is given, and the diagnosis suggestion is written into a diagnosis report by a reporting doctor. That is, the sonographer must observe both dynamic video streaming images and still pictorial images. At present, artificial intelligence technology in the field of image recognition is based on image pixel processing. Common images such as bmp, jpg, png, etc. are stored with R, G, B three bytes per pixel. An image with 1920 × 1080 resolution consists of 1920 × 1080 pixels, and totally consists of 1920 × 1080 × 3 bytes, and each byte consists of 8 bits, that is, RGB values range from 0 to 255. If only one of 1920 × 1080 × 3 × 8 bits is different, the two images are different, and ai is considered to be two images, the pixel values are different, and the prediction result is likely to be different, but no difference is observed with the naked human eye. In order to save storage space, a common image storage format is jpg, which is lossy compression, and has a high compression rate and a small picture.
Since the sonographer needs to observe both the dynamic video stream image and the static picture image, but jpg has a lossy compression, the original pixel value cannot be restored, the decompressed value is different from the original image in the memory, and the jpg image is imported again, so that the ai identification result is different. The doctor may review the patient or perform scientific research in the future, and may review the previously stored images again, and at this time, the ai identification result is different from the previous identification result, which may cause instability of the product, and may cause troubles to the doctor, or even mislead the doctor, resulting in medical accidents.
In some embodiments, as shown in fig. 2, the image processing and displaying method further includes, S201, saving the frame extraction image, and simultaneously saving the frame extraction image as a static png picture.
Preferably, the image processing and displaying method further includes:
s201, inputting the static png picture into an ai model to obtain a second image with detected and segmented coordinate points and a classification result;
and S203, sending the static png picture and the second image to a client side for display through an http protocol.
In this embodiment, the stored still picture is in the lossless compression format png, the pixel value decompressed again is the same as the pixel value of the original image, and for ai, the image is the same image, and the recognition result is the same, so that the current diagnosis result and the re-diagnosis result performed by ai are ensured to be the same.
As shown in fig. 3, an embodiment of the present invention provides a video stream processing display system, including:
an ultrasound device 100 connected to the video acquisition apparatus 201 by a video line;
a linux ultrasound ai host 200, wherein a video acquisition device 201 is installed on the ultrasound ai host, and the video acquisition device 201 is used for acquiring a dynamic video stream of the ultrasound equipment 100; the ultrasonic ai host 200 directly acquires the video stream from the video acquisition card, and the problem of network frame loss does not exist.
The linux ultrasonic ai host 200 captures a trigger event, stores a frame extraction image in a memory, and locally stores a static png picture at the same time by using the handle key 300. Capturing a trigger event means that the linux ultrasonic ai host 200 receives a working instruction of the handle key 300;
in this embodiment, the video capture card is installed on the ultrasound ai host, and the ultrasound device is connected to the video capture on the ultrasound ai host through a video line such as an HDMI video line, so as to realize that the ultrasound ai host captures a display imaging picture of the ultrasound device. Through the physical architecture, the ultrasonic ai host can obtain video streams and picture images of the ultrasonic equipment, so that doctors are assisted in dynamic video examination and static image examination.
As shown in fig. 4, an embodiment of the present invention provides a video stream processing display apparatus, including:
a first image obtaining module 20, configured to input a frame-extracted image of an original video stream into an ai model, so as to obtain a first image with detected and segmented coordinate points and classification results;
a target video stream obtaining module 40, configured to encode the first image and the non-frame-extracted image of the original video stream into a target video stream;
and a first pushing module 60, configured to push the target video stream to the client for display through rtsp.
Optionally, the apparatus further comprises:
the saving module 201 is configured to save the frame extraction image, and save the frame extraction image as a static png picture.
In the embodiment, a video stream processing and displaying apparatus is provided, where a first image obtaining module 20 inputs the frame-extracted image into an ai model to obtain a first image with detected and segmented coordinate points and classification results; the target video stream obtaining module 40 encodes the non-frame-extracted image and the first image into a target video stream; the first pushing module 60 pushes the target video stream to the client for displaying through rtsp, so that the accuracy of analyzing images by a doctor is improved, and the real-time performance of the acquired images is ensured. Because the stored static picture is in a lossless compression format png, the pixel value decompressed again is the same as that of the original image, and for ai, the image is the same image, and the recognition result is the same, so that the current diagnosis result and the repeated diagnosis result of ai are ensured to be the same.
In some embodiments, as shown in fig. 5, the video stream processing display device further includes:
a second image obtaining module 202, configured to input the static png picture into an ai model, so as to obtain a second image with the detected and segmented coordinate points and the classification result;
and the second pushing module 203 is configured to send the static png picture and the second image to the client through an http protocol for display.
In this embodiment, the stored still picture is in the lossless compression format png, the pixel value decompressed again is the same as the pixel value of the original image, and for ai, the image is the same image, and the recognition result is the same, so that the current diagnosis result and the re-diagnosis result performed by ai are ensured to be the same.
An electronic device is also provided in the embodiments of the present application, and fig. 6 shows a schematic structural diagram of an electronic device to which the embodiments of the present application can be applied, and as shown in fig. 6, the computer electronic device includes a Central Processing Unit (CPU)701 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)702 or a program loaded from a storage section 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data necessary for the operation of the system 700 are also stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
The following components are connected to the I/O interface 705: an input section 1006 including a keyboard, a mouse, and the like; an output section 707 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 708 including a hard disk and the like; and a communication section 709 including a network interface card such as a LAN card, a modem, or the like. The communication section 709 performs communication processing via a network such as the internet. The drive 310 is also connected to the I/O interface 705 as needed. A removable medium 711 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 710 as necessary, so that a computer program read out therefrom is mounted into the storage section 708 as necessary.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The application also provides a computer readable storage medium, which can be the computer readable storage medium contained in the video stream processing display system in the above embodiment; or it may be a computer-readable storage medium that exists separately and is not built into the electronic device. The computer-readable storage medium stores one or more programs for use by one or more processors in performing the video stream processing display method described herein.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A video stream processing display method for assisting diagnosis of a doctor, comprising the steps of:
processing an original video stream to obtain a frame extraction image and a frame extraction-free image;
inputting the frame-extracted image into an ai model to obtain a first image with detected and segmented coordinate points and a classification result;
encoding the non-decimated image and the first image into a target video stream;
and pushing the target video stream to a client for displaying through an rtsp.
2. The video stream processing display method of claim 1, wherein inputting the decimated image into an ai model to obtain a first image with detected and segmented coordinate points and classification results comprises:
inputting the frame-extracted image into an ai model to classify, detect and segment the focus;
and drawing the detected and segmented coordinate points and the classification result on the frame-drawing image to obtain a first image.
3. The method according to claim 2, further comprising saving the decimated image while saving the decimated image as a static png picture.
4. The video stream processing display method according to any one of claim 3, wherein the image processing display method further comprises:
inputting the static png picture into an ai model to obtain a second image with detected and segmented coordinate points and a classification result;
and sending the static png picture and the second image to a client side for display through an http protocol.
5. A video stream processing display system, characterized in that the image processing display system comprises:
an ultrasound device connected to the video acquisition device by a video line;
the ultrasonic device comprises a linux ultrasonic ai host, wherein the ultrasonic ai host is provided with a video acquisition device, and the video acquisition device is used for acquiring dynamic video streams of the ultrasonic equipment;
and the linux ultrasonic ai host captures a trigger event, stores a frame extraction image in the memory and locally stores a static png picture at the same time.
6. A video stream processing display apparatus, characterized in that the apparatus comprises:
the first image acquisition module is used for inputting the frame-extracted image of the original video stream into the ai model to obtain a first image with detected and segmented coordinate points and classification results;
the target video stream acquisition module is used for encoding the frame-not-extracted image and the first image of the original video stream into a target video stream;
and the first pushing module is used for pushing the target video stream to the client side for displaying through rtsp.
7. The video stream processing display device according to claim 6, wherein the device further comprises:
and the storage module is used for storing the frame extraction image and simultaneously storing the frame extraction image as a static png picture.
8. The video stream processing display device according to claim 7, further comprising:
the second image acquisition module is used for inputting the static png picture into an ai model to obtain a second image with detected and segmented coordinate points and classification results;
and the second pushing module is used for sending the static png picture and the second image to a client side for displaying through an http protocol.
9. An electronic device, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor implements the method of any one of claims 1-4 by executing the executable instructions.
10. A computer readable storage medium having stored thereon computer instructions which, when executed by a processor, carry out the steps of the method according to any one of claims 1 to 4.
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