CN114782323A - Medical image acquisition and analysis method and device, storage medium and electronic equipment - Google Patents
Medical image acquisition and analysis method and device, storage medium and electronic equipment Download PDFInfo
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Abstract
The embodiment of the application provides a medical image acquisition and analysis method, a device, a storage medium and electronic equipment, wherein the method comprises the following steps: analyzing the current scientific research analysis requirement to obtain a target disease condition meeting the scientific research analysis requirement; detecting the disease condition of the original medical image through an AI detection system; acquiring an original medical image with a target disease condition from the AI detection result, and labeling the original medical image with the target disease condition; and acquiring a target image which has a label and accords with the target disease condition from the original medical image so as to carry out scientific research and analysis based on the target image. The AI detection system detects a large amount of original medical images, labels the original medical images with target conditions in AI detection results, classifies the original medical images, and can quickly acquire required images from the original medical images according to the labels, so that follow-up scientific research and analysis on the images are facilitated.
Description
Technical Field
The present disclosure relates to the field of medical image classification, and in particular, to a method, an apparatus, a storage medium, and an electronic device for acquiring and analyzing medical images.
Background
The AI detection result includes information such as medical image and disease description. In general, after the AI-assisted detection, the detection result may be output. Then, the AI detection result is often used as basic data for medical research, so a large amount of case reports for AI detection need to be collected, and after preprocessing, the AI detection data is comprehensively analyzed to be used as important basic data for medical research.
In the actual data collection process, all AI detection data are not collected for preprocessing and analysis, but important and special AI detection data (disease conditions of special types such as lesion deformity and scattered plaque) need to be manually screened for summarization, and the workload of summarizing the screening data is very large, which can cause fatigue of doctors and image the normal work of the doctors.
Therefore, the prior art has defects and needs to be improved and developed.
Disclosure of Invention
The embodiment of the application provides a medical image acquisition and analysis method and device, a storage medium and electronic equipment, which can quickly acquire a required target medical image from a large number of medical images, so that subsequent scientific research and analysis aiming at the target medical image are facilitated.
The embodiment of the application provides a medical image acquisition and analysis method, which comprises the following steps:
analyzing the current scientific research analysis requirement to obtain a target disease condition meeting the scientific research analysis requirement;
detecting the disease condition of the original medical image through an AI detection system;
acquiring an original medical image with the target disease condition from an AI detection result, and labeling the original medical image with the target disease condition;
and acquiring a target image which has the label and accords with the target disease condition from the original medical image so as to carry out scientific research analysis based on the target image.
In the medical image acquiring and analyzing method according to the embodiment of the present application, after acquiring the target image with the target disease state from the AI detection result and labeling the target image, the method further includes:
and generating a corresponding original medical report based on the AI detection result and the original medical image, wherein the label is set in the original medical image with the target disease condition in the original medical report.
In the medical image acquisition and analysis method according to the embodiment of the present application, in an original medical report corresponding to an original medical image having the label, a description of a disease condition corresponding to a target disease condition of the original medical image is recorded;
the obtaining of the target image having the label and conforming to the target condition from the original medical image comprises:
and identifying the disease description content in the original medical report, and acquiring the original medical image which is matched with the target disease and has the label as a target image according with the target disease.
In the medical image acquiring and analyzing method according to the embodiment of the present application, the acquiring a target image having the label and conforming to the target condition from the original medical image includes:
and acquiring the original medical image with the label from the original medical image as a target image according with the target disease condition.
In the medical image acquisition and analysis method according to the embodiment of the present application, the label of the original medical image includes a description content of a corresponding preset condition;
the obtaining of the target image having the label and conforming to the target condition from the original medical image comprises:
and matching the label of the original medical image with the target disease condition, and determining the successfully matched original medical image as a target image according with the target disease condition.
In the medical image acquiring and analyzing method according to the embodiment of the present application, the detecting a disease condition includes a lesion detection, and the acquiring an original medical image with the target disease condition from an AI detection result and labeling the original medical image with the target disease condition includes:
acquiring an original medical image with a preset focus from an AI detection result, and labeling the original medical image with the preset focus;
the method further comprises the following steps:
and if the original medical image in the AI detection result has an unknown focus, identifying a target part where the unknown focus is located in the original medical image.
In the medical image acquiring and analyzing method according to the embodiment of the present application, after acquiring the target image having the tag and conforming to the target disease condition from the AI detection result, the method further includes:
judging whether the data volume of the acquired target image is enough or not;
if not, identifying the original medical image with the target part based on a preset identification model, and determining a focus identification result of each target part;
and acquiring the original medical image of which the focus identification result accords with the target disease condition as the target image.
The embodiment of the present application further provides a medical image acquisition and analysis device, the device includes:
the analysis module is used for analyzing the current scientific research analysis requirement to obtain a target illness state meeting the scientific research analysis requirement;
the detection module is used for detecting the disease condition of the original medical image through the AI detection system;
the first acquisition module is used for acquiring an original medical image with the target disease state from an AI detection result and labeling the original medical image with the target disease state;
and the second acquisition module is used for acquiring a target image which has the label and accords with the target disease condition from the original medical image so as to perform scientific research and analysis based on the target image.
The embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored, and when the computer program runs on a computer, the computer is enabled to execute the medical image acquisition and analysis method according to any embodiment.
The embodiment of the present application further provides an electronic device, where the electronic device includes a processor and a memory, where the memory stores a computer program, and the processor calls the computer program stored in the memory to execute the medical image acquisition and analysis method according to any embodiment.
The AI detection system detects a large amount of original medical images, labels the original medical images with target conditions in AI detection results, classifies the original medical images, and can quickly acquire the required target medical images from the original medical images according to the labels, so that subsequent scientific research and analysis on the target medical images are facilitated.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the application, and that for a person skilled in the art, other drawings can also be derived from them without inventive effort.
Fig. 1 is a schematic flow chart of a medical image acquisition and analysis method according to an embodiment of the present application.
Fig. 2 is a schematic structural diagram of a medical image acquisition and analysis apparatus according to an embodiment of the present disclosure.
Fig. 3 is a schematic structural diagram of another medical image acquisition and analysis apparatus according to an embodiment of the present disclosure.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. It is to be understood that the embodiments described are only a few embodiments of the present application and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without inventive step, are within the scope of the present application.
The embodiment of the application provides a medical image acquisition and analysis method, which can be applied to electronic equipment.
Referring to fig. 1, fig. 1 is a schematic flow chart of a medical image acquisition and analysis method according to an embodiment of the present application. The medical image acquisition and analysis method is applied to electronic equipment, and the method can comprise the following steps:
The target condition may be a specific condition, such as unilateral coronary artery, calcification, and vascular malformation, among others.
And 102, detecting the disease condition of the original medical image through an AI detection system.
Wherein, the disease detection can be focus detection.
In some embodiments, before the performing the disease detection on the original medical image by the AI detection system, the method further comprises:
an original medical image is acquired.
In which, the physiological structure of the human body can be scanned by using Computed Tomography (CT) images, Magnetic Resonance examination (MR) images, 4D ultrasound images, and the like, so as to obtain an original medical image. The human physiological structures may be heart, liver, lung, blood vessels and bones, etc.
For example, if the target disease condition is a vascular abnormality, an original medical image with the vascular abnormality is obtained from the AI detection result, and a label of "C" is marked on the original medical image for subsequent scientific analysis.
And 104, acquiring a target image which has the label and accords with the target disease condition from the original medical image so as to perform scientific research and analysis based on the target image.
The original medical image has a label, which indicates that the original medical image has a target disease condition, but since the target disease condition may include a plurality of disease conditions and the scientific research analysis requirement may only need to analyze one disease condition, the target image not only needs to have a label, but also needs to meet the scientific research analysis requirement.
For example, the target condition includes unilateral coronary artery, calcification and vascular malformation, corresponding to labels A, B and C, respectively, and scientific analysis requires that the original medical image with label C be obtained as the target image from the original medical image instead of obtaining the original medical image with label a or label B as the target image.
And sending the collected (integrated) target image to a scientific research analysis system for scientific research analysis to obtain an analysis result. The method comprises the following preferable steps: and simultaneously, acquiring images of normal cases to form a contrast set. And sending the target image of the special focus and the image of the normal case to a scientific research analysis system or a scientific research analysis mechanism for scientific research analysis. For example, the normal calcified structure is M-shaped, the special calcified structure is N-shaped, and scientific research is facilitated through comparative analysis.
In some embodiments, obtaining an original medical image with the target condition from the AI detection result and labeling the original medical image with the target condition further comprises:
and generating a corresponding original medical report based on the AI detection result and the original medical image, wherein the label is set in the original medical image with the target disease condition in the original medical report.
In some embodiments, a medical condition description corresponding to a target medical condition of the original medical image is recorded in an original medical report corresponding to the original medical image with the label.
For example, if the original medical image 1 has the label C corresponding to the blood vessel abnormality, the original medical report corresponding to the original medical image 1 having the label C has the description of the disease condition corresponding to the blood vessel abnormality of the original medical image 1.
In some embodiments, the obtaining a target image having the label and corresponding to the target condition from the original medical image comprises:
and identifying the disease description content in the original medical report, and acquiring the original medical image which is matched with the target disease and has the label as a target image according with the target disease.
For example, if the target disease condition is a vascular abnormality, identifying the disease condition description content in the original medical report, and acquiring an original medical image with the disease condition description content being the vascular abnormality and having a label as a target image meeting the requirements of scientific research and analysis.
In some embodiments, the acquiring, from the original medical image, a target image having the label and corresponding to the target condition includes:
and acquiring the original medical image with the label from the original medical image as a target image according with the target disease condition.
However, in the original medical report corresponding to the original medical image, the content related to the preset medical condition corresponding to the label is not recorded, and in this case, the original medical image with the label only needs to be obtained from the original medical image as the target image meeting the requirement of scientific research analysis.
For example, if the original medical image is labeled to indicate that the AI detection result has a blood vessel abnormality, the original medical report corresponding to the original medical image may not record the content of the blood vessel abnormality corresponding to the label, and when the scientific research analysis requirement is to analyze the blood vessel abnormality, the original medical image with the label only needs to be acquired from the original medical image as the target image meeting the scientific research analysis requirement (to analyze the blood vessel abnormality).
In some embodiments, the label of the original medical image includes a description of the corresponding predetermined medical condition;
the obtaining of the target image having the label and conforming to the target condition from the original medical image comprises:
and matching the label of the original medical image with the target disease condition, and determining the successfully matched original medical image as the target image according with the target disease condition.
Because the label of the original medical image already comprises the description content of the corresponding preset disease condition, when the target image is to be obtained from the original medical image, the label of the original medical image only needs to be matched with the target disease condition, the successfully matched original medical image is determined to be the target image meeting the requirements of scientific research and analysis, and the target image does not need to be obtained by identifying the description content of the disease condition in the original medical report.
In some embodiments, the disease condition detection comprises a lesion detection, and the obtaining of the original medical image with the target disease condition from the AI detection result and the labeling of the original medical image with the target disease condition comprises:
acquiring an original medical image with a preset focus from an AI detection result, and labeling the original medical image with the preset focus;
the method further comprises the following steps:
and if the original medical image in the AI detection result has an unknown focus, identifying a target part where the unknown focus is located in the original medical image.
The predetermined lesion may be a specific lesion, such as a unilateral coronary artery, calcification, vascular malformation, etc. Since the AI detection result can only determine that the original medical image has a focus, but what focus is not detected, the target region where the unknown focus is located in the original medical image is identified for the next operation.
In some embodiments, after obtaining the target image with the tag and according with the target disease condition from the AI detection result, the method further includes:
judging whether the data volume of the acquired target image is enough or not;
if not, identifying the original medical image with the target part based on a preset identification model, and determining a focus identification result of each target part;
and acquiring the original medical image of which the lesion recognition result accords with the target disease condition as the target image.
The data volume of the target image is not enough, and the original medical image with the target part may also belong to the target image, so that the original medical image with the target part can be identified through a preset identification model, the focus identification result of each target part is determined, and then the original medical image with the focus identification result meeting the scientific research and analysis requirements is obtained as the target image, thereby complementing the data volume of the target image.
All the above optional technical solutions may be combined arbitrarily to form optional embodiments of the present application, and are not described in detail herein.
In specific implementation, the present application is not limited by the execution sequence of the described steps, and some steps may be performed in other sequences or simultaneously without conflict.
As can be seen from the above, the medical image acquisition and analysis method provided in the embodiment of the present application performs disease detection on a large number of original medical images through the AI detection system, and performs labeling processing on the original medical images with preset disease conditions in the AI detection result to classify the original medical images, and then only needs to obtain a required target medical image from the large number of medical images quickly according to the label, thereby facilitating subsequent scientific research and analysis on the target medical image.
The embodiment of the application further provides a medical image acquisition and analysis device, which can be integrated in an electronic device.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a medical image acquisition and analysis apparatus according to an embodiment of the present application. The medical image acquisition and analysis device 30 may include:
the analysis module 31 is used for analyzing the current scientific research analysis requirement to obtain a target illness state meeting the scientific research analysis requirement;
the detection module 32 is used for detecting the disease condition of the original medical image through an AI detection system;
a first obtaining module 33, configured to obtain an original medical image with the target disease condition from an AI detection result, and perform labeling processing on the original medical image with the target disease condition;
a second obtaining module 34, configured to obtain a target image that has the label and meets the target condition from the original medical image, so as to perform scientific research analysis based on the target image.
In some embodiments, the first obtaining module 33 is configured to obtain an original medical image with a predetermined lesion from an AI detection result, and perform labeling processing on the original medical image with the predetermined lesion.
In some embodiments, the second obtaining module 34 is configured to identify the disease description in the original medical report, and obtain the original medical image with the label matching the target disease as the target image corresponding to the target disease.
In some embodiments, the second acquiring module 34 is configured to acquire the original medical image with the label from the original medical images as a target image corresponding to the target condition.
In some embodiments, the second acquiring module 34 is configured to match the label of the original medical image with the target medical condition, and determine the successfully matched original medical image as the target image corresponding to the target medical condition.
In specific implementation, the modules may be implemented as independent entities, or may be combined arbitrarily and implemented as one or several entities.
As can be seen from the above, the medical image acquisition and analysis device 30 provided in the embodiment of the present application analyzes the current scientific research analysis requirement through the analysis module 31 to obtain a target disease condition meeting the scientific research analysis requirement; the detection module 32 detects the condition of an original medical image through an AI detection system; acquiring an original medical image with the target disease condition from the AI detection result through a first acquisition module 33, and labeling the original medical image with the target disease condition; and acquiring a target image which has the label and accords with the target disease condition from the original medical image through a second acquisition module 34 so as to perform scientific research analysis based on the target image. The AI detection system detects a large amount of original medical images, labels the original medical images with preset conditions in AI detection results, classifies the original medical images, and can quickly acquire required target medical images from the large amount of medical images according to the labels, so that subsequent scientific research and analysis aiming at the target medical images are facilitated.
Referring to fig. 3, fig. 3 is another schematic structural diagram of a medical image acquisition and analysis apparatus according to an embodiment of the present disclosure, in which the medical image acquisition and analysis apparatus 30 includes a memory 120, one or more processors 180, and one or more application programs, where the one or more application programs are stored in the memory 120 and configured to be executed by the processor 180; the processor 180 may include a first acquisition module 31, a processing module 32, a second acquisition module 33, and a third acquisition module 34. For example, the structures and connection relationships of the above components may be as follows:
the memory 120 may be used to store applications and data. The memory 120 stores applications containing executable code. The application programs may constitute various functional modules. The processor 180 executes various functional applications and data processing by running the application programs stored in the memory 120. Further, the memory 120 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Accordingly, the memory 120 may also include a memory controller to provide the processor 180 with access to the memory 120.
The processor 180 is a control center of the device, connects various parts of the entire terminal using various interfaces and lines, performs various functions of the device and processes data by running or executing an application program stored in the memory 120 and calling data stored in the memory 120, thereby monitoring the entire device. Optionally, processor 180 may include one or more processing cores; preferably, the processor 180 may integrate an application processor and a modem processor, wherein the application processor mainly processes an operating system, a user interface, an application program, and the like.
Specifically, in this embodiment, the processor 180 loads the executable code corresponding to the process of one or more application programs into the memory 120 according to the following instructions, and the processor 180 runs the application programs stored in the memory 120, thereby implementing various functions:
the analysis module 31 is used for analyzing the current scientific research analysis requirement to obtain a target illness state meeting the scientific research analysis requirement;
the detection module 32 is used for detecting the disease condition of the original medical image through an AI detection system;
a first obtaining module 33, configured to obtain an original medical image with the target disease condition from an AI detection result, and perform labeling processing on the original medical image with the target disease condition;
a second obtaining module 34, configured to obtain a target image that has the label and meets the target condition from the original medical image, so as to perform scientific research analysis based on the target image.
In some embodiments, the first obtaining module 33 is configured to obtain an original medical image with a predetermined lesion from an AI detection result, and perform labeling processing on the original medical image with the predetermined lesion.
In some embodiments, the second obtaining module 34 is configured to identify the disease description in the original medical report, and obtain the original medical image with the label matching the target disease as the target image corresponding to the target disease.
In some embodiments, the second acquiring module 34 is configured to acquire the original medical image with the label from the original medical images as a target image corresponding to the target condition.
In some embodiments, the second acquiring module 34 is configured to match the label of the original medical image with the target medical condition, and determine the successfully matched original medical image as the target image corresponding to the target medical condition.
The embodiment of the application also provides the electronic equipment.
Referring to fig. 4, fig. 4 is a schematic structural diagram of an electronic device provided in an embodiment of the present application, where the electronic device may be used to implement the medical image acquisition and analysis method provided in the foregoing embodiment.
As shown in fig. 4, the electronic device 1200 may include components such as an RF (Radio Frequency) circuit 110, a memory 120 including one or more (only one shown) computer-readable storage media, an input unit 130, a display unit 140, a sensor 150, an audio circuit 160, a transmission module 170, a processor 180 including one or more (only one shown) processing cores, and a power supply 190. Those skilled in the art will appreciate that the configuration of the electronic device 1200 shown in FIG. 4 is not intended to be limiting of the electronic device 1200 and may include more or fewer components than shown, or some components may be combined, or a different arrangement of components. Wherein:
the RF circuit 110 is used for receiving and transmitting electromagnetic waves, and implementing interconversion between the electromagnetic waves and electrical signals, so as to communicate with a communication network or other devices. The RF circuitry 110 may include various existing circuit elements for performing these functions, such as an antenna, a radio frequency transceiver, a digital signal processor, an encryption/decryption chip, a Subscriber Identity Module (SIM) card, memory, and so forth. The RF circuitry 110 may communicate with various networks such as the internet, an intranet, a wireless network, or with other devices over a wireless network.
The memory 120 may be configured to store software programs and modules, such as program instructions/modules corresponding to the medical image acquisition and analysis method in the foregoing embodiment, and the processor 180 may execute various functional applications and data processing by running the software programs and modules stored in the memory 120, so as to quickly acquire a desired target medical image from a large number of medical images, thereby facilitating subsequent scientific research and analysis on the target medical image. Memory 120 may include high speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 120 may further include memory remotely located from the processor 180, which may be connected to the electronic device 1200 through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input unit 130 may be used to receive input numeric or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control. In particular, the input unit 130 may include a touch-sensitive surface 131 as well as other input devices 132. The touch-sensitive surface 131, also referred to as a touch display screen or a touch pad, may collect touch operations by a user on or near the touch-sensitive surface 131 (e.g., operations by a user on or near the touch-sensitive surface 131 using a finger, a stylus, or any other suitable object or attachment), and drive the corresponding connection device according to a predetermined program. Alternatively, the touch sensitive surface 131 may comprise two parts, a touch detection means and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device, converts the touch information into touch point coordinates, sends the touch point coordinates to the processor 180, and receives and executes commands sent from the processor 180. Additionally, the touch sensitive surface 131 may be implemented using various types of resistive, capacitive, infrared, and surface acoustic waves. In addition to touch-sensitive surface 131, input unit 130 may include other input devices 132. In particular, other input devices 132 may include, but are not limited to, one or more of a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, a joystick, and the like.
The display unit 140 may be used to display information input by or provided to a user and various graphic user interfaces of the electronic device 1200, which may be configured by graphics, text, icons, video, and any combination thereof. The Display unit 140 may include a Display panel 141, and optionally, the Display panel 141 may be configured in the form of an LCD (Liquid Crystal Display), an OLED (Organic Light-Emitting Diode), or the like. Further, the touch-sensitive surface 131 may cover the display panel 141, and when a touch operation is detected on or near the touch-sensitive surface 131, the touch operation is transmitted to the processor 180 to determine the type of the touch event, and then the processor 180 provides a corresponding visual output on the display panel 141 according to the type of the touch event. Although in FIG. 3, touch-sensitive surface 131 and display panel 141 are shown as two separate components to implement input and output functions, in some embodiments, touch-sensitive surface 131 may be integrated with display panel 141 to implement input and output functions.
The electronic device 1200 may also include at least one sensor 150, such as light sensors, motion sensors, and other sensors. Specifically, the light sensor may include an ambient light sensor that may adjust the brightness of the display panel 141 according to the brightness of ambient light, and a proximity sensor that may turn off the display panel 141 and/or the backlight when the electronic device 1200 is moved to the ear. As one of the motion sensors, the gravity acceleration sensor can detect the magnitude of acceleration in each direction (generally, three axes), can detect the magnitude and direction of gravity when the mobile phone is stationary, and can be used for applications of recognizing the posture of the mobile phone (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer and tapping), and the like; as for other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which may be further configured in the electronic device 1200, detailed descriptions thereof are omitted.
The audio circuitry 160, speaker 161, microphone 162 may provide an audio interface between a user and the electronic device 1200. The audio circuit 160 may transmit the electrical signal converted from the received audio data to the speaker 161, and convert the electrical signal into a sound signal for output by the speaker 161; on the other hand, the microphone 162 converts the collected sound signal into an electric signal, converts the electric signal into audio data after being received by the audio circuit 160, and then outputs the audio data to the processor 180 for processing, and then to the RF circuit 110 to be transmitted to, for example, another terminal, or outputs the audio data to the memory 120 for further processing. The audio circuitry 160 may also include an earbud jack to provide communication of peripheral headphones with the electronic device 1200.
The electronic device 1200, via the transport module 170 (e.g., Wi-Fi module), may assist the user in emailing, browsing web pages, accessing streaming media, etc., which provides the user with wireless broadband internet access. Although fig. 4 shows the transmission module 170, it is understood that it does not belong to the essential constitution of the electronic device 1200, and may be omitted entirely as needed within the scope not changing the essence of the invention.
The processor 180 is a control center of the electronic device 1200, connects various parts of the entire cellular phone using various interfaces and lines, performs various functions of the electronic device 1200 and processes data by operating or executing software programs and/or modules stored in the memory 120 and calling data stored in the memory 120. Optionally, processor 180 may include one or more processing cores; in some embodiments, the processor 180 may integrate an application processor, which primarily handles operating systems, user interfaces, applications, etc., and a modem processor, which primarily handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 180.
The electronic device 1200 also includes a power supply 190 (e.g., a battery) that powers the various components, and in some embodiments, may be logically coupled to the processor 180 via a power management system to manage charging, discharging, and power consumption management functions via the power management system. The power supply 190 may also include any component including one or more dc or ac power sources, recharging systems, power failure detection circuitry, power converters or inverters, power status indicators, and the like.
Although not shown, the electronic device 1200 may further include a camera (e.g., a front camera, a rear camera), a bluetooth module, and the like, which are not described in detail herein. Specifically in this embodiment, the display unit 140 of the electronic device 1200 is a touch screen display, the electronic device 1200 further comprises a memory 120, and one or more programs, wherein the one or more programs are stored in the memory 120, and the one or more programs are configured to be executed by the one or more processors 180 and comprise instructions for:
analyzing the current scientific research analysis requirement to obtain a target disease condition meeting the scientific research analysis requirement;
detecting the disease condition of the original medical image through an AI detection system;
acquiring an original medical image with the target disease condition from an AI detection result, and labeling the original medical image with the target disease condition;
and acquiring a target image which has the label and accords with the target disease condition from the original medical image so as to perform scientific research and analysis based on the target image.
In some embodiments, the processor 180 is configured to generate a corresponding original medical report based on the AI detection result and the original medical image, wherein the label is set on the original medical image having the target condition in the original medical report.
In some embodiments, the processor 180 is configured to identify the condition description in the original medical report, and obtain the original medical image matching the target condition and having the tag as the target image corresponding to the target condition.
In some embodiments, the processor 180 is configured to obtain the original medical image with the label from the original medical images as a target image corresponding to the target condition.
In some embodiments, the processor 180 is configured to match the label of the original medical image with the target medical condition, and determine the original medical image successfully matched with the label as the target image corresponding to the target medical condition.
In some embodiments, the processor 180 is configured to identify a target region in the original medical image where the unknown lesion is located if the original medical image has an unknown lesion in the AI detection result.
In some embodiments, the processor 180 is configured to determine whether the data amount of the acquired target image is sufficient;
if not, identifying the original medical image with the target part based on a preset identification model, and determining a focus identification result of each target part;
and acquiring the original medical image of which the focus identification result accords with the target disease condition as the target image.
As can be seen from the above, an embodiment of the present application provides an electronic device 1200, where the electronic device 1200 executes the following steps: analyzing the current scientific research analysis requirement to obtain a target disease condition meeting the scientific research analysis requirement; detecting the disease condition of the original medical image through an AI detection system; acquiring an original medical image with the target disease condition from an AI detection result, and labeling the original medical image with the target disease condition; and acquiring a target image which has the label and accords with the target disease condition from the original medical image so as to perform scientific research and analysis based on the target image.
The embodiment of the present application further provides a storage medium, where a computer program is stored, and when the computer program runs on a computer, the computer executes the medical image acquisition and analysis method according to any one of the embodiments.
It should be noted that, for the medical image acquisition and analysis method described in the present application, it can be understood by a person skilled in the art that all or part of the processes for implementing the medical image acquisition and analysis method described in the present application can be implemented by controlling the relevant hardware through a computer program, where the computer program can be stored in a computer readable storage medium, such as a memory of an electronic device, and executed by at least one processor in the electronic device, and during the execution process, the processes of the embodiment of the medical image acquisition and analysis method can be included. The storage medium may be a magnetic disk, an optical disk, a Read Only Memory (ROM), a Random Access Memory (RAM), or the like.
In the medical image acquisition and analysis apparatus according to the embodiment of the present application, each functional module may be integrated in one processing chip, or each module may exist alone physically, or two or more modules are integrated in one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium, such as a read-only memory, a magnetic or optical disk, or the like.
The medical image acquisition and analysis method, the medical image acquisition and analysis device, the storage medium and the electronic device provided by the embodiment of the application are described in detail above. The principle and the implementation of the present application are explained herein by applying specific examples, and the above description of the embodiments is only used to help understand the method and the core idea of the present application; meanwhile, for those skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (10)
1. A method for acquiring and analyzing medical images, the method comprising:
analyzing the current scientific research analysis requirement to obtain a target disease condition meeting the scientific research analysis requirement;
detecting the disease condition of the original medical image through an AI detection system;
acquiring an original medical image with the target disease condition from an AI detection result, and labeling the original medical image with the target disease condition;
and acquiring a target image which has the label and accords with the target disease condition from the original medical image so as to perform scientific research and analysis based on the target image.
2. The method of claim 1, wherein the step of obtaining an original medical image with the target condition from AI detection results and labeling the original medical image with the target condition further comprises:
and generating a corresponding original medical report based on the AI detection result and the original medical image, wherein the label is set in the original medical image with the target disease condition in the original medical report.
3. The method according to claim 2, wherein a medical condition description corresponding to a target medical condition of the original medical image is recorded in an original medical report corresponding to the original medical image having the label;
the obtaining of the target image having the label and conforming to the target condition from the original medical image comprises:
and identifying the disease description content in the original medical report, and acquiring the original medical image which is matched with the target disease and has the label as a target image according with the target disease.
4. The method for medical image acquisition and analysis according to claim 1, wherein the acquiring a target image having the label and corresponding to the target condition from the original medical image comprises:
and acquiring the original medical image with the label from the original medical image as a target image according with the target disease condition.
5. The method according to claim 1, wherein the label of the original medical image comprises a description of a corresponding predetermined medical condition;
the obtaining of the target image having the label and conforming to the target condition from the original medical image comprises:
and matching the label of the original medical image with the target disease condition, and determining the successfully matched original medical image as a target image according with the target disease condition.
6. The method of claim 1, wherein the disease detection comprises a lesion detection, the obtaining of the original medical image with the target disease from the AI detection result and the labeling of the original medical image with the target disease comprises:
acquiring an original medical image with a preset focus from an AI detection result, and labeling the original medical image with the preset focus;
the method further comprises the following steps:
if the original medical image in the AI detection result has an unknown focus, identifying a target part where the unknown focus is located in the original medical image.
7. The method of claim 6, wherein the obtaining the target image with the label and corresponding to the target condition from the AI test result further comprises:
judging whether the data volume of the acquired target image is enough or not;
if not, identifying the original medical image with the target part based on a preset identification model, and determining a focus identification result of each target part;
and acquiring the original medical image of which the focus identification result accords with the target disease condition as the target image.
8. A medical image acquisition and analysis apparatus, the apparatus comprising:
the analysis module is used for analyzing the current scientific research analysis requirement to obtain a target illness state meeting the scientific research analysis requirement;
the detection module is used for detecting the disease condition of the original medical image through an AI detection system;
the first acquisition module is used for acquiring an original medical image with the target disease condition from an AI detection result and labeling the original medical image with the target disease condition;
and the second acquisition module is used for acquiring a target image which has the label and accords with the target disease condition from the original medical image so as to carry out scientific research analysis based on the target image.
9. A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program runs on a computer, the computer is caused to execute the medical image acquisition and analysis method according to any one of claims 1 to 7.
10. An electronic device, comprising a processor and a memory, wherein the memory stores a computer program, and the processor is configured to execute the medical image acquisition and analysis method according to any one of claims 1 to 7 by calling the computer program stored in the memory.
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| CN202210315579.5A CN114782323A (en) | 2022-03-28 | 2022-03-28 | Medical image acquisition and analysis method and device, storage medium and electronic equipment |
| CN202310316463.8A CN116797535A (en) | 2022-03-28 | 2023-03-28 | Medical data acquisition method, medical data acquisition device, computer equipment and storage medium |
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