A method and system for marking the position of a target part

Abstract

The present application discloses a method and system for marking the position of a target part. The method comprises: acquiring image information of a target part of a target object; processing the image information to determine the position of the target part within the target object; and marking a medical image of the target object based on the position information. This application provides a method for identifying and marking a target part, which can improve the accuracy and efficiency of target part marking, thereby facilitating medical work.

Description

Technical Field

[0001] The present application relates to the field of medical image technology, and in particular to a method and system for marking the position of a target part in a medical image. Background Art

[0002] Medical imaging devices are increasingly used in clinical diagnosis and treatment. Doctors analyze medical images corresponding to target patient areas to make pathological diagnoses. In some scenarios, medical images may only capture one bilaterally symmetrical body part. For example, a medical imaging device may capture a patient's left knee. In this case, to provide accurate information to doctors, the medical image needs to be labeled to indicate the specific orientation of the image.

[0003] Therefore, there is an urgent need for a target site identification and marking method that can improve the accuracy and operational efficiency of target site marking and provide convenience for medical work. Summary of the Invention

[0004] One embodiment of the present application provides a method for marking the position of a target part. The method comprises: acquiring image information of a target part of a target object; processing the image information to determine the position information of the target part in the target object; and marking a medical image of the target object based on the position information.

[0005] One of the embodiments of the present application provides a target part orientation marking system, the system comprising: an image information acquisition module for acquiring image information of a target part of a target object; an orientation information determination module for processing the image information and determining the orientation information of the target part in the target object; and an orientation information marking module for marking a medical image of the target object based on the orientation information.

[0006] One embodiment of the present application provides a device for marking the position of a target part, including a processor, wherein the processor is used to execute computer instructions to implement a method for marking the position of the target part.

[0007] One of the embodiments of the present application provides a system for marking the orientation of a target part, the system comprising: a camera device for acquiring image information of the target object; a medical imaging device for acquiring a medical image of the target object; an information processing device for processing the image information to determine the orientation information of the target part; and marking the orientation information in the medical image. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The present application will be further described in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, like numbers represent like structures, wherein:

[0009] Figure 1 is a schematic diagram of application scenarios according to some embodiments of this specification;

[0010] Figure 2 is an exemplary flow chart of a target position marking system according to some embodiments of the present specification;

[0011] Figure 3 is an exemplary flow chart of marking a target position according to some embodiments of the present application;

[0012] Figure 4 is a schematic diagram of a medical image according to some embodiments of the present application;

[0013] Figure 5 is a schematic diagram of a medical image according to some other embodiments of the present application. DETAILED DESCRIPTION

[0014] To more clearly illustrate the technical solutions of the embodiments of this application, the following is a brief introduction to the drawings required for describing the embodiments. Obviously, the drawings described below are merely examples or embodiments of this application. Those skilled in the art can apply this application to other similar scenarios based on these drawings without inventive effort. Unless otherwise apparent from the context or otherwise noted, the same reference numerals in the figures represent the same structure or operation.

[0015] It should be understood that the terms "system," "device," "unit," and / or "module" used herein are a method for distinguishing different components, elements, parts, portions, or assemblies at different levels. However, if other terms can achieve the same purpose, the terms may be replaced by other expressions.

[0016] As used in this application and the claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" are not intended to refer to the singular but may include the plural. Generally speaking, the terms "comprises" and "include" only indicate the inclusion of the steps and elements specifically identified, and these steps and elements do not constitute an exclusive list. A method or apparatus may also include other steps or elements.

[0017] Flowcharts are used in this application to illustrate the operations performed by the systems according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, the steps may be processed in reverse order or simultaneously. Furthermore, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0018] In some embodiments, manual identification and labeling of the imaging site in the medical image are required. In some embodiments, the physician can also select a corresponding imaging protocol based on the known imaging site during the actual imaging process, and the medical imaging device can label the position information according to the selected protocol. This process may result in errors in judgment, calibration, or protocol selection, which could impact the diagnosis and subsequent treatment.

[0019] In response to the above problems, some embodiments of the present application provide a target part orientation marking system, which obtains image information of the target object and processes the image information based on a preset algorithm to determine the orientation information of the target part in the target object, and then marks the medical image of the target part based on the orientation information.

[0020] The target location marking system provided in the embodiments of the present application is described in detail below with reference to the accompanying drawings.

[0021] Figure 1 It is a schematic diagram of application scenarios shown in some embodiments of this specification.

[0022] like Figure 1 As shown, the position marking system 100 may include a medical imaging device 110, a network 120, a processing device 140, a storage device 150, and an imaging device 160. In some embodiments, the system 100 may further include at least one terminal 130. The various components in the system 100 may be interconnected via the network 120. For example, the medical imaging device 110 and the processing device 140 may be connected or communicated via the network 120.

[0023] In some embodiments, the imaging device 160 is used to capture image information containing the target object. In some embodiments, the imaging device 160 can be an optical device, such as a camera or other image sensor. In some embodiments, the imaging device 160 can also be a non-optical device that, based on the acquired distance data, generates a thermal map that can reflect characteristics such as the shape and size of the target object. In some embodiments, the imaging device 160 can capture both still images and video images.

[0024] In some embodiments, the medical imaging device 110 can collect data from a target subject to obtain a medical image of a target area of ​​the target subject. In some embodiments, the medical imaging device can include a digital radiography (DR) imaging device, a computed tomography (CT) scanner, a magnetic resonance imaging (MRI) scanner, a b-scan ultrasonography scanner, a thermal texture maps (TTM) scanner, or a positron emission tomography (PET) scanner. For example, the medical imaging device 110 is described using a CT scanner as an example. For example, if the system analyzes the image information obtained by the imaging device 160 and determines that the target area is the left knee, the target subject can lie flat on the scanning bed 1101 with their face facing upward. The scanning bed 1101 is then moved so that the left knee is within the scanning area to obtain a medical image of the left knee.

[0025] Network 120 may comprise any suitable network capable of facilitating information and / or data exchange within system 100. In some embodiments, at least one component of system 100 (e.g., medical imaging device 110, processing device 140, storage device 150, imaging device 160, at least one terminal 130) may exchange information and / or data with at least one other component of system 100 via network 120. For example, processing device 140 may obtain image information from medical imaging device 110 via network 120. For another example, processing device 140 may obtain instructions from a user (e.g., a physician) from at least one terminal 130 via network 120. Network 120 may comprise or include a public network (e.g., the Internet), a private network (e.g., a local area network (LAN)), a wired network, a wireless network (e.g., an 802.11 network, a Wi-Fi network), a frame relay network, a virtual private network (VPN), a satellite network, a telephone network, a router, a hub, a switch, a server computer, and / or any combination thereof. For example, the network 120 may include a wired network, a cable network, a fiber optic network, a telecommunications network, an intranet, a wireless local area network (WLAN), a metropolitan area network (MAN), a public switched telephone network (PSTN), a Bluetooth™ network, a ZigBee™ network, a near field communication (NFC) network, or the like, or any combination thereof. In some embodiments, the network 120 may include at least one network access point. For example, the network 120 may include a wired and / or wireless network access point, such as a base station and / or an Internet exchange point, and at least one component of the system 100 may connect to the network 120 via the access point to exchange data and / or information.

[0026] In some embodiments, at least one terminal 130 can communicate and / or connect with the medical imaging device 110, the camera 160, the processing device 140, and / or the storage device 150. For example, the at least one terminal 130 can obtain the position analysis results of the target area from the processing device 140 or obtain captured image information from the camera 160. For another example, the at least one terminal 130 can receive user operation instructions and then send the operation instructions to the medical imaging device 110 or the camera 160 to control them (e.g., adjust the image acquisition angle, set operating parameters of the medical imaging device, etc.). In some embodiments, the at least one terminal 130 can include a mobile device 130-1, a tablet computer 130-2, a laptop computer 130-3, etc., or any combination thereof. For example, the mobile device 130-1 can include a mobile phone, a personal digital assistant (PDA), a medical device, etc., or any combination thereof. In some embodiments, the at least one terminal 130 can include input devices, output devices, etc. The input device can include alphanumeric and other keys for inputting control instructions to control the medical imaging device 110 and / or the camera 160. The input device may be a keyboard input, a touch screen (e.g., with tactile or haptic feedback) input, a voice input, a gesture input, or any other similar input mechanism. The input information received by the input device may be transmitted to the processing device 140 via a bus, for example, for further processing. Other types of input devices may include a cursor control device, such as a mouse, a trackball, or cursor direction keys. The output device may include a display, a speaker, a printer, or any combination thereof, for outputting the medical images captured by the medical imaging device 110 and / or the image information captured by the camera 160. In some embodiments, at least one terminal 130 may be part of the processing device 140.

[0027] The processing device 140 can process data and / or instructions obtained from the medical imaging device 110, the storage device 150, the at least one terminal 130, or other components of the system 100. For example, the processing device 140 can obtain image information of a target object from the imaging device 160 and process the image information to obtain position information of a target part of the target object.

[0028] In some embodiments, processing device 140 may be a single server or a server group. The server group may be centralized or distributed. In some embodiments, processing device 140 may be local or remote. For example, processing device 140 may access information and / or data from medical imaging device 110, storage device 150, and / or at least one terminal 130 via network 120. For another example, processing device 140 may be directly connected to medical imaging device 110, at least one terminal 130, and / or storage device 150 to access information and / or data. In some embodiments, processing device 140 may be implemented on a cloud platform. For example, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud cloud, a multi-cloud, or any combination thereof.

[0029] In some embodiments, the medical imaging device 110 may perform scanning based on the position information of the target part on the target object determined by the processing device 140. For example, the medical imaging device 110 may scan the target part (e.g., the left knee) based on the position information of the target part of the target object (e.g., the left knee) processed by the processing device 140, thereby obtaining a medical image of the target part.

[0030] The storage device 150 can store data, instructions, and / or any other information. In some embodiments, the storage device 150 can store image information captured by the medical imaging device 110. In some embodiments, the storage device 150 can store data obtained from the medical imaging device 110, the at least one terminal 130, and / or the processing device 140. In some embodiments, the storage device 150 can also store a correspondence between a target part and position information, and the processing device 140 can derive the position information of the target part based on this correspondence and the processed target part. In some embodiments, the storage device 150 can store data and / or instructions used by the processing device 140 to execute or complete the exemplary methods described herein. In some embodiments, the storage device 150 can include mass storage, removable storage, volatile read-write memory, read-only memory (ROM), or any combination thereof. Exemplary mass storage can include magnetic disks, optical disks, solid-state disks, etc. Exemplary removable storage can include flash drives, floppy disks, optical disks, memory cards, compact disks, magnetic tapes, etc. Exemplary volatile read-write memory can include random access memory (RAM). In some embodiments, the storage device 150 can be implemented on a cloud platform.

[0031] In some embodiments, storage device 150 may be connected to network 120 to communicate with at least one other component in system 100 (e.g., processing device 140, at least one terminal 130). At least one component in system 100 may access data or instructions stored in storage device 150 via network 120. In some embodiments, storage device 150 may be part of processing device 140.

[0032] One or more embodiments of the present specification provide a method and system for marking the position of a target site. Figure 2 FIG2 is an exemplary flow chart of a target position marking system according to some embodiments of the present specification. In some embodiments, the control system may include an image information acquisition module, a position information determination module, and a position information marking module.

[0033] The image information acquisition module is used to acquire image information of a target part of a target object.

[0034] The position information determination module is used to process the image information and determine the position information of the target part in the target object.

[0035] A position information marking module is configured to mark the medical image of the target object based on the position information. In some embodiments, the position information marking module is further configured to: obtain a medical image of the target area; and mark the position information in the medical image. In some embodiments, the position information marking module is further configured to: determine corresponding protocol information based on the position information; and mark the medical image of the target area based on the protocol information.

[0036] In some embodiments, the process 200 may be performed by a target site location marking system, and the process 200 includes:

[0037] Step 210: Acquire image information of the target object. In some embodiments, step 210 may be performed by an image information acquisition module.

[0038] The target object includes an object for which a medical image is to be captured, for example, a patient.

[0039] Image information refers to an image of a target object (e.g., a human body and its parts or organs) acquired by a camera device. In some embodiments, the image may include a static image or a video image of the target object. In some embodiments, the static image may include a still image such as a photograph or a picture. In some embodiments, a video image refers to a dynamic image, which may include but is not limited to a video, an animation, etc. In some embodiments, a video stream may be derived from a video image, and the video stream may include multiple frames of static images. In some embodiments, the image may be an optical image or a non-optical image. In some embodiments, it may be an optical device, such as a camera, or other image sensor. In some embodiments, the camera device may also be a non-optical device, which obtains a thermal map that can reflect the shape, size, and other features of the target object based on a number of distance data collected.

[0040] In some embodiments, the camera device may include any device with a two-dimensional or three-dimensional image capture function. In some embodiments, the image information includes at least the positioning information of the target part of the target object relative to the medical imaging device, and the processor may determine the target part based on the positioning information. In some embodiments, the positioning information includes whether there is an object to be detected in the radiation irradiation area of ​​the medical imaging device, or whether there is an object to be detected on the placement table (for example, a hospital bed) of the medical imaging device. The placement table or the radiation irradiation area can be regarded as a positionable area, and the object to be detected in the positionable area can be regarded as the target part to be detected of the target object.

[0041] In some embodiments, the medical imaging device can also be adjusted based on the image information of the target site so that the target site is in the radiation path of the radiation source. In some embodiments, the operation of adjusting the medical imaging device can be performed manually or automatically by a machine. In some embodiments, adjusting the medical imaging device can include adjusting the radiation source of the medical imaging device, or can include adjusting the detector of the medical imaging device, or can include adjusting both the detector and the radiation source. This specification does not limit this, as long as the target site can be placed in the radiation path of the radiation source after the adjustment.

[0042] In some embodiments, when the target object adjusts the posture and / or position of the target part so as to place it in the ray path of the ray source of the medical imaging device, it can be determined that the target part is within the positionable area.

[0043] In some embodiments, the target portion can be determined during the process of manually or automatically adjusting the movement of the radiation source of the medical imaging device to align with the target portion. For example, if a patient has entered the imaging area of ​​the medical imaging device for positioning, and the target portion is now located to the left of the radiation source of the medical imaging device, the target portion can be adjusted to move to the right so that it is in the radiation path of the radiation source of the medical imaging device, or the radiation source of the medical imaging device can be adjusted to move to the left so that the target portion is in the radiation path of the radiation source of the medical imaging device. During this process, the processor can determine the target portion in the positionable area based on the collected image information (e.g., video information corresponding to the process).

[0044] The image information acquisition module can acquire image information captured by the camera device via wired or wireless communication and further identify target objects in the image information. In some embodiments, the system can derive a video stream from the input video image and perform frame-by-frame processing. In some embodiments, the processing can include filtering and denoising the image, normalizing the image grayscale, horizontally rotating the image, correcting the image scale, etc. In some embodiments, the processing can also include identifying or segmenting the target object or target part in the image.

[0045] Step 220: Process the image information to determine the position information of the target part. In some embodiments, step 220 may be performed by a position information determination module.

[0046] In some embodiments, the target site may include the entire or a portion of a tissue or organ of the target subject. For example, the target site may include the left ankle joint, chest, etc.

[0047] In some embodiments, the position information of the target part includes at least one of the left and right position, the up and down position, and the front and back position of the target part relative to the target object. In some embodiments, the position information of the target part relative to the target object includes left and right position information, for example, the left knee joint. In some embodiments, the position information of the target part relative to the target object includes up and down information, for example, the upper spine. In some embodiments, the position information of the target part relative to the target object includes front and back position information, for example, the back. In some embodiments, the position information of the target part relative to the target object is left and right up and down information, for example, the target part is the upper left hip joint.

[0048] In some embodiments, the orientation information of the target part may also include the direction of the ray incidence in the medical imaging device, etc. The ray incidence direction in the medical imaging device may include the positional relationship between the direction of the initial ray incidence and the target object or target part. For example, if the target part for which a medical image needs to be taken is the left hand, then the orientation information may include the hand located on the left side of the body, and may also include whether the back of the hand faces the direction of the initial ray incidence, or whether the palm faces the direction of the initial ray incidence. For another example, if the target part for which a medical image needs to be taken on a DR scanner is the left thigh, then the orientation information may include the thigh located on the left side of the body, and may also include whether the target object's face faces the direction of the initial ray incidence, or whether the target object faces the direction of the initial ray incidence, that is, whether the patient lies flat on the scanning bed facing the direction of the initial ray incidence, or lies flat on the scanning bed with his back facing the direction of the initial ray incidence.

[0049] In some embodiments, the orientation information determination module receives image information of a target part of a target object through a network, and can identify the image of the target part according to a preset algorithm, process the image information, and determine the orientation information of the target part. For example, in the continuous process of shooting video images, the camera device captures all images including the process of positioning the patient to exposing the patient. In this process, the radiation source and / or the display table and / or the camera can be configured to be movable, and the orientation information determination module can automatically identify the orientation information of the target part. For example, in the process of shooting an X-ray of the left knee joint through DR, the camera device captures that the medical imaging device moves the radiation source to the top of the left knee joint, then the orientation information determination module can analyze and identify in real time that the target part is the left knee joint.

[0050] In some embodiments, the preset algorithm may include an algorithm for image processing and analysis. Specifically, the preset algorithm first performs image segmentation and other processing on the image of the target object obtained by the camera device, and then determines the position of the target part in the image based on the positional relationship between the target part in the image and the medical imaging device, and then analyzes and determines the orientation information of the target part relative to the target object.

[0051] In some embodiments, the preset algorithm may include an image matching algorithm. Specifically, the image matching algorithm calculates the degree of match between the image information of the target object obtained by the camera device and the image information in the associated database, selects the image information with the highest degree of match as the obtained image information, and further analyzes and determines the orientation information of the target part relative to the target object. In some embodiments, the image matching method includes grayscale-based image matching and feature-based image matching.

[0052] In some embodiments, the preset algorithm may further include a machine learning model. Specifically, the image of the target object obtained by the camera device is input into a trained machine learning model, and the orientation information of the target part is determined based on the output data of the machine learning model. In some embodiments, the output data of the machine learning model may include the name of the target part and its corresponding orientation information, for example, the left knee joint. In some embodiments, the image information obtained by the camera device may be preprocessed to filter out higher-quality images, which may be images with higher clarity or images containing all target objects with the target part in position. The filtered images are then input into the machine learning model, and the machine learning model may automatically output the orientation information of the target part relative to the target object based on the input data.

[0053] In some embodiments, the machine learning model may include a deep neural network (DNN), such as a convolutional neural network (CNN), a deep belief network (DBN), a random Boolean network (RBN), etc. The deep learning model may include a multi-layer neural network structure. Taking a convolutional neural network as an example, a convolutional neural network may include an input layer, a convolution layer, a dimensionality reduction layer, a hidden layer, an output layer, etc. The convolutional neural network includes one or more convolution kernels for convolution operations.

[0054] In some embodiments, the initial machine learning model can be trained using training sample data to obtain a trained machine learning model. The training sample data can include several historical images of the target object, and the historical images need to include images of the target part. The target part and its orientation information in the historical images are marked. For example, the marked information of the target part may include the left knee joint. The historical image information is then used as input data, and the marked information of the orientation information is used as the corresponding output data or criterion. The input data and output data are then input into the initial machine learning model for training to obtain a trained model.

[0055] Step 230: Mark the medical image of the target object based on the position information.

[0056] The system obtains a medical image of the target object through a medical imaging device, and the orientation information marking module marks the corresponding orientation information on the obtained medical image. In some embodiments, the medical image of the target object may include a medical image corresponding to the target part on the target object. In some embodiments, the medical image of the target object may also include a medical image corresponding to the non-target part on the target object. The non-target part can be understood as a part that has a certain correlation with the target part. For example, if the target part is a palm, the non-target part can be the arm corresponding to the palm, and the orientation information of the palm of the target object can be marked on the medical image of the target object's arm.

[0057] In some embodiments, a medical image can be understood as an image obtained by a medical imaging device. In some embodiments, the medical imaging device may include a DR imaging device, a CT scanner, an MRI scanner, a B-imaging scanner, a TTM scanner, a SPECT device, or a PET scanner. Correspondingly, in some embodiments, the medical image includes at least one of MRI, XR, PET, SPECT, CT, and ultrasound images. In some embodiments, the medical image information may also include a fusion image of one or more of the aforementioned medical images. In some embodiments, the image information and the medical image may be obtained simultaneously or sequentially.

[0058] In some embodiments, the marking can be a color, text, or graphic. More specifically, it can be a combination of one or more Chinese characters, English characters, or graphic characters. In some embodiments, each medical image can include one or more markings. For example, an image of the right knee joint can be marked with R. Optionally, each medical image can also include one or more location-related markings.

[0059] In some embodiments, the markers may be manually adjusted. In some embodiments, the manual adjustment may include adding one or more marker points, deleting one or more markers, changing the position of one or more markers, and the like.

[0060] In some embodiments, the position information marking module may directly mark the medical image based on the position information of the target part, as described in detail in steps 231a and 232a below. In other embodiments, the position information marking module may select a scanning protocol based on the position information of the target part to acquire the medical image and further mark the medical image, as described in detail in steps 231b and 232b below.

[0061] Step 231a: Acquire a medical image of the target object.

[0062] In some embodiments, a medical image can be understood as an image acquired by a medical imaging device. In some embodiments, the medical image may include an MRI image, a CT image, a cone-beam CT image, a PET image, a functional MRI image, an X-ray image, a fluoroscopic image, an ultrasound image, a SPECT image, or any combination thereof. The medical image may reflect information about a portion of a patient's tissue, organ, and / or bone. In some embodiments, the medical image is one or a group of two-dimensional images, such as black-and-white X-ray film, such as a two-dimensional CT scan image. In some embodiments, the medical image may be a three-dimensional image, such as a three-dimensional image of an organ reconstructed from CT scan images of different slices, or a three-dimensional spatial image output by a device with three-dimensional imaging capabilities. In some embodiments, the medical image may also be a dynamic image over a period of time, such as a video that reflects the changes in the heart and its surrounding tissues during a cardiac cycle. In some embodiments, the medical image may be obtained from a medical imaging device, a storage module, or user input via an interactive device.

[0063] In some embodiments, the medical imaging device uses the medical imaging device to acquire a medical image of the target part according to the obtained position information, and marks the position information in the obtained medical image.

[0064] Step 232a: Mark the position information in the medical image.

[0065] In some embodiments, the orientation information can be marked at a certain position in the medical image. For example, the orientation information can be marked at the upper left corner of the image. Herein, marking the orientation information in the medical image can be understood as marking directly in the medical image in a displayable manner, for example, covering a local area of ​​the medical image; for example, adding a description to the medical image to be able to display the orientation information of the target part in the medical image. In order not to affect the doctor's observation of the target part, the position of the mark is generally set at the peripheral position of the medical image. In some embodiments, the content of the mark may only include the orientation information of the target part, and the doctor can determine the name of the target part through the corresponding medical image. For example, the content of the mark can be: right side, or it can be represented by the English letter R, for example Figure 4 In some embodiments, the content of the mark may include the name of the target part and its location information. For example, the content of the mark may be the right ankle, or it may be represented by the English letters RIGHT ANKLE, for example Figure 5 shown.

[0066] Step 231b: Determine corresponding protocol information based on the position information.

[0067] In some embodiments, the system selects a corresponding protocol based on the positional information of the target area, then examines the target area of ​​the subject according to the protocol, obtaining a medical image of the target area captured by a medical imaging device. In some embodiments, the protocol refers to a combination of imaging parameters of the medical imaging device, and the corresponding protocol is selected for the target area captured by a patient. For example, if the left knee joint or chest is imaged using DR, the protocol for the left knee joint or chest is selected during the scan.

[0068] Step 232b: Mark the medical image based on the protocol information.

[0069] In some embodiments, the system further tags the medical image according to the selected protocol. In some embodiments, the system detects the protocol used and further tags the position information in the protocol used onto the medical image or its perspective content.

[0070] In some embodiments, the markings of already marked medical images can be adjusted. This adjustment can include manual adjustment or automatic machine adjustment. For example, if a doctor finds that at least one of the marking content, marking location, and marking method of the marking information on the medical image is inappropriate, the doctor can manually adjust it. For another example, a machine can automatically check the marking information on the medical image and automatically adjust any inappropriate marking information to ensure the accuracy of the marking information.

[0071] It should be noted that the above description of the flowchart is for ease of description only and does not limit the present application to the scope of the embodiments illustrated. It is understood that those skilled in the art, after understanding the present application, may make various modifications and changes to the application form and details of the above-mentioned method and system without departing from the principles herein. However, such modifications and changes remain within the scope of the above description. For example, the system can directly identify the target part without identifying the target object.

[0072] Figure 3 This is an exemplary flowchart of marking the target position according to some embodiments of the present application.

[0073] The process can be performed by a system for marking the position of a target part, wherein the system uses a medical imaging device to acquire a medical image of the target part and marks the generated position information of the target part in the medical image. In some embodiments, the system includes: an imaging device for acquiring image information of the target object; a medical imaging device for acquiring a medical image of the target part on the target object; an information processing device for processing the image information based on a preset algorithm to determine the position information of the target part; and marking the position information in the medical image.

[0074] In some embodiments, the target object is first positioned, and the camera begins capturing images. The image information acquisition module analyzes the captured images and determines whether a patient is detected in the images captured by the camera. In some embodiments, whether a patient is detected indicates whether the captured images contain the patient and whether the target part of the patient is within the positionable area.

[0075] When the camera can clearly capture the patient and the target area is within the positionable area, positioning is complete, meaning the patient can be detected. For example, using a CT scanner as an example, the target object (e.g., a patient) is first positioned within the medical imaging device. The patient is placed on the CT scanner bed. The patient's posture and / or position on the bed, as well as the bed position, are adjusted so that, for example, when scanning a topography film, the CT scanner's radiation beam partially or completely passes through the target area of ​​the target object. During the patient positioning process and / or after positioning is completed, before and / or during bed entry, and / or while scanning the topography film, the camera simultaneously captures image information. The image information acquisition module analyzes the captured image information. If the analysis captures image information containing the patient and the target area is within the positionable area, positioning of the patient is complete.

[0076] If the patient cannot be detected in the images captured by the camera, or the detected target area of ​​the patient is not within the positionable area, the patient's posture or position and / or the scanning table position must be adjusted again and new image information must be acquired. This process continues until the image information acquisition module is able to analyze and obtain image information containing the patient and the target object is within the positionable area, indicating that positioning is complete. For example, using a mammography machine, when a patient stands in front of the machine, they compress their breast between the detector housing and the compressor, allowing some or all of the radiation beam to pass through the breast. The camera captures image information of this process, and the image information acquisition module analyzes the acquired image information. If the analysis can obtain image information containing the patient, positioning is complete.

[0077] In some embodiments, after the positioning is completed, the information processing device analyzes the data to obtain orientation information, and the system automatically completes marking on the captured medical image based on the analysis results.

[0078] In some embodiments, the camera device can be relatively fixed or movably arranged on the medical imaging device; in some embodiments, the camera device can also be independently arranged outside the medical imaging device. In this case, during the image acquisition process, the camera device can be fixed or movable. In some embodiments, the camera device can be located on a movable part of the medical imaging device, or on a movable part integrated on the medical imaging device. For example, the camera device can be located on the C-arm or the frame of the breast machine. For another example, a track can be fixed on the frame, and the camera device can move on the track. After the patient's positioning is completed, the orientation information determination module analyzes the image information according to a preset algorithm (for example, a machine learning model) to obtain the target part, and further analyzes and generates the orientation information of the target part.

[0079] In some embodiments, the imaging device and the medical imaging device can be connected to each other via a wired or wireless connection. In some embodiments, the imaging device is a camera.

[0080] The beneficial effects that may be brought about by the embodiments of the present application include but are not limited to: (1) processing and analyzing the image information based on a preset algorithm to obtain the orientation information of the target part, thereby improving the accuracy of the orientation information recognition; (2) using a machine to automatically recognize the orientation information of the target position and mark it based on the recognized orientation information, thereby improving the accuracy of the marking operation; (3) using a machine to automatically recognize and mark the target part in the medical image, thereby achieving automation and intelligence and improving operational efficiency. It should be noted that different embodiments may produce different beneficial effects. In different embodiments, the beneficial effects that may be produced may be any one or a combination of the above, or any other possible beneficial effects.

[0081] The basic concepts have been described above. It will be apparent to those skilled in the art that the detailed disclosure above is merely illustrative and does not limit the present application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and amendments to the present application. Such modifications, improvements, and amendments are suggested in the present application and remain within the spirit and scope of the exemplary embodiments of the present application.

[0082] At the same time, this application uses specific terms to describe the embodiments of this application. For example, "one embodiment," "an embodiment," and / or "some embodiments" refer to a certain feature, structure, or characteristic related to at least one embodiment of this application. Therefore, it should be emphasized and noted that "one embodiment," "an embodiment," or "an alternative embodiment" mentioned twice or multiple times in different locations in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of this application may be appropriately combined.

[0083] In addition, it will be understood by those skilled in the art that various aspects of the present application can be illustrated and described by a number of patentable categories or situations, including any new and useful process, machine, product or combination of substances, or any new and useful improvements thereto. Accordingly, various aspects of the present application can be performed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The above hardware or software may all be referred to as "data blocks", "modules", "engines", "units", "components" or "systems". In addition, various aspects of the present application may be represented as a computer product located in one or more computer-readable media, which includes computer-readable program code.

[0084] A computer storage medium may include a propagated data signal embodying the computer program code, for example, in baseband or as part of a carrier wave. The propagated signal may be in a variety of forms, including electromagnetic, optical, or any suitable combination thereof. A computer storage medium may be any computer-readable medium other than a computer-readable storage medium that can be connected to an instruction execution system, apparatus, or device to communicate, propagate, or transfer the program for use. The program code on the computer storage medium may be transmitted via any suitable medium, including radio, cable, fiber optic cable, RF, or similar media, or any combination of these.

[0085] The computer program code required for the operation of each part of the present application can be written in any one or more programming languages, including object-oriented programming languages ​​such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB.NET, Python, etc., conventional procedural programming languages ​​such as C language, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, dynamic programming languages ​​such as Python, Ruby and Groovy, or other programming languages. The program code can be run entirely on the user's computer, or as a separate software package on the user's computer, or partly on the user's computer and partly on a remote computer, or entirely on a remote computer or server. In the latter case, the remote computer can be connected to the user's computer through any network form, such as a local area network (LAN) or a wide area network (WAN), or connected to an external computer (e.g., via the Internet), or in a cloud computing environment, or used as a service such as software as a service (SaaS).

[0086] In addition, unless expressly stated in the claims, the order of the processing elements and sequences described in this application, the use of alphanumeric characters, or the use of other names are not intended to limit the order of the processes and methods of this application. Although the above disclosure discusses some of the invention embodiments currently considered useful through various examples, it should be understood that such details are only for illustrative purposes, and the attached claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the essence and scope of the embodiments of this application. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only by software solutions, such as installing the described system on an existing server or mobile device.

[0087] Similarly, it should be noted that, in order to simplify the presentation of this application and thus facilitate understanding of one or more embodiments of the invention, the foregoing descriptions of the embodiments of this application sometimes combine multiple features into a single embodiment, figure, or description thereof. However, this disclosure method does not mean that the subject matter of this application requires more features than those recited in the claims. In fact, an embodiment may have fewer features than all of the features of a single embodiment disclosed above.

[0088] In some embodiments, numbers are used to describe the quantity of components and attributes. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise stated, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the description and claims are approximate values, which may change according to the required features of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of the present application are approximate values, in specific embodiments, the settings of such numerical values ​​are as accurate as possible within the feasible range.

[0089] Each patent, patent application, patent application disclosure, and other materials, such as articles, books, specifications, publications, documents, etc., cited in this application is hereby incorporated by reference in its entirety. This includes application history documents that are inconsistent with or conflict with the content of this application, as well as documents (currently or subsequently attached to this application) that limit the broadest scope of the claims of this application. It should be noted that if the descriptions, definitions, and / or use of terms in the accompanying materials of this application are inconsistent or conflicting with the content of this application, the descriptions, definitions, and / or use of terms in this application shall prevail.

[0090] Finally, it should be understood that the embodiments described in this application are merely illustrative of the principles of the embodiments of this application. Other variations may also fall within the scope of this application. Therefore, by way of example and not limitation, alternative configurations of the embodiments of this application may be considered consistent with the teachings of this application. Accordingly, the embodiments of this application are not limited to the embodiments explicitly introduced and described in this application.

Claims

1. A method for marking the position of a target part, characterized in that: The method comprises: Acquiring image information of a target part of a target object; Processing the image information through a machine learning model to determine the position information of a target part in the target object includes: Inputting the image information into the machine learning model; Determining the target part and the position information of the target part based on the output data of the machine learning model, wherein the object to be detected in the radiation irradiation area or the display table of the medical imaging device is determined as the target part of the target object; the position information includes at least one of the left-right position, the up-down position, and the front-back position of the target part relative to the target object; determining corresponding protocol information based on the position information; Scanning the target part using the medical imaging device according to the protocol information to obtain a medical image of the target part; The position information in the protocol information is marked on the medical image.

2. The method according to claim 1, characterized in that The orientation information includes at least one of a left-right orientation, a front-back orientation, and an up-down orientation of the target part relative to the target object.

3. The method according to claim 1, characterized in that The image information of the target object includes a static image or a video image.

4. The method according to claim 1, wherein The image information is obtained by a camera, and the medical image is an image of MRI, XR, PET, SPECT, CT, or ultrasound, or a fusion image of two or more.

5. The method according to claim 1, wherein Based on the image information of the target part, the radiation source of the medical imaging device is automatically adjusted so that the target part is located in the radiation path of the radiation source.

6. The method according to claim 1, characterized in that The medical image of the target object is marked based on the position information, including marking with color, text, or graphics.

7. The method according to claim 1, characterized in that Manual adjustment of labels for labeled medical images is also included.

8. A target location marking system, characterized in that: The system comprises: An image information acquisition module, used to acquire image information of a target part of a target object; A position information determination module is used to process the image information through a machine learning model to determine the position information of the target part of the target object, including: Inputting the image information into the machine learning model; Determining the target part and the position information of the target part based on the output data of the machine learning model, wherein the object to be detected in the radiation irradiation area or the display table of the medical imaging device is determined as the target part of the target object; the position information includes at least one of the left-right position, the up-down position, and the front-back position of the target part relative to the target object; A position information marking module, configured to determine corresponding protocol information based on the position information; Scanning the target part using the medical imaging device according to the protocol information to obtain a medical image of the target part; The position information in the protocol information is marked on the medical image.

9. The system according to claim 8, characterized in that The system further includes a camera for acquiring the image information, wherein the medical image is an image of MRI, XR, PET, SPECT, CT, or ultrasound, or a fusion image of two or more.

10. A device for marking the position of a target part, comprising a processor, characterized in that: The processor is configured to execute computer instructions to implement the method according to any one of claims 1 to 9.

11. A system for marking the position of a target part, characterized in that: The system comprises: a camera device, configured to obtain image information of a target part of the target object; A medical imaging device for acquiring medical images of a target object; An information processing device, configured to process the image information using a machine learning model to determine the position information of a target part of the target object, comprising: Inputting the image information into the machine learning model; Determining the target part and the position information of the target part based on the output data of the machine learning model, wherein the object to be detected in the radiation irradiation area or the display table of the medical imaging device is determined as the target part of the target object; the position information includes at least one of the left-right position, the up-down position, and the front-back position of the target part relative to the target object; determining corresponding protocol information based on the position information; Scanning the target part using the medical imaging device according to the protocol information to obtain a medical image of the target part; The position information in the protocol information is marked on the medical image.

12. The system according to claim 11, wherein: The imaging device is relatively fixedly or movably arranged on the medical imaging device.

13. The system according to claim 11, wherein: The imaging device is a camera.

Images