Target region positioning method, electronic device, and medium

Abstract

The present disclosure provides a target region positioning method, an electronic device and a computer readable storage medium, the target region positioning method comprising: acquiring, by a camera, a target image comprising a skin surface region corresponding to a reaction bone; wherein the reaction bone is a bone having a target feature; identifying the skin surface region from the target image; determining first device coordinate information of a center position of the skin surface region in a device coordinate system; determining second device coordinate information of a center position of a target region comprising a lesion in the device coordinate system according to the first device coordinate information and predetermined first position relationship information; wherein the first position relationship information is position relationship information between the center position of the skin surface region and the center position of the target region.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the field of smart medical technology, and in particular to a method for locating a target area, an electronic device, and a computer-readable storage medium. Background Art

[0002] Minimally invasive treatment techniques use image-guided, minimally invasive methods such as focused ultrasound, cryosurgery, catheter-based intervention, and radiofrequency ablation to precisely destroy and eliminate tumors. With the continuous advancement of medical technology, minimally invasive treatments, characterized by minimal trauma, precise efficacy, targeted treatment, and rapid recovery, have become one of the most active and promising technologies in comprehensive oncology treatment. However, due to the complex internal structure of the patient's anatomy, the treatment requires a high level of expertise in locating the patient's lesion. This, especially for inexperienced physicians, can take a significant amount of time, limiting many physicians' involvement in minimally invasive treatment. Furthermore, the determination of the patient's lesion is largely subjective, leading to potential errors in positioning the patient. Furthermore, if the patient's position changes during treatment, the physician must rely on experience to reposition the patient, further consuming the time.

[0003] In order to reduce the workload of doctors and reduce the dependence of surgical operations on doctors' experience, it is necessary to intelligently identify the location of patients' lesions. The current intelligent recognition technology requires the use of sticky markings, which will increase patients' discomfort. In addition, the selection of marking materials and training on the sticking location also increase the workload of medical staff.

[0004] Public content

[0005] Embodiments of the present disclosure provide a method for locating a target area, an electronic device, and a computer-readable storage medium.

[0006] In a first aspect, an embodiment of the present disclosure provides a method for locating a target area, including:

[0007] Capturing a target image including a skin surface area corresponding to a reactive bone through a camera; wherein the reactive bone is a bone having a target feature;

[0008] identifying the skin surface area from the target image;

[0009] Determine first device coordinate information of a center position of the skin surface area in a device coordinate system;

[0010] Determine the second device coordinate information of the center position of the target area including the lesion in the device coordinate system based on the first device coordinate information and the predetermined first position relationship information; wherein the first position relationship information is the position relationship information between the center position of the skin surface area and the center position of the target area.

[0011] In some exemplary embodiments, identifying the skin surface area from the target image comprises:

[0012] performing image enhancement processing on the target image;

[0013] The target image after image enhancement processing is input into the trained classification model to obtain the first pixel coordinate information of the skin surface area in the pixel coordinate system.

[0014] In some exemplary embodiments, before inputting the target image after image enhancement processing into a trained classification model to obtain first pixel coordinate information of the skin surface area in a pixel coordinate system, the method further includes:

[0015] collecting a sample image including the skin surface area by the camera;

[0016] performing image enhancement processing on the sample image;

[0017] The classification model is obtained by performing model training based on the sample images after image enhancement processing.

[0018] In some exemplary embodiments, determining first device coordinate information of the center position of the skin surface area in a device coordinate system includes:

[0019] Determining second pixel coordinate information of the center position of the skin surface area in a pixel coordinate system;

[0020] Determining camera coordinate information of the center position of the skin surface area in a camera coordinate system according to the second pixel coordinate information and a first conversion relationship; wherein the first conversion relationship is a conversion relationship between the pixel coordinate system and the camera coordinate system;

[0021] The first device coordinate information is determined according to the camera coordinate information and a second conversion relationship; wherein the second conversion relationship is a conversion relationship between the camera coordinate system and the device coordinate system.

[0022] In some exemplary embodiments, the first position relationship information is a difference between the first device coordinate information and fourth device coordinate information of the center position of the target area in the device coordinate system;

[0023] The second device coordinate information of the center position of the target area including the lesion in the device coordinate system determined according to the first device coordinate information and the predetermined first position relationship information includes:

[0024] The second device coordinate information is determined to be a difference between the first device coordinate information and the first position relationship information.

[0025] In some exemplary embodiments, before acquiring the target image including the skin surface area corresponding to the reactive bone through the camera, the method further comprises:

[0026] The first position relationship information is obtained in advance based on the nuclear magnetic resonance image.

[0027] In some exemplary embodiments, the obtaining the first position relationship information in advance based on the nuclear magnetic resonance image includes:

[0028] Determining first nuclear magnetic coordinate information of the center position of the target area in a nuclear magnetic coordinate system and second nuclear magnetic coordinate information of the target position of the reaction bone in the nuclear magnetic coordinate system according to the nuclear magnetic image;

[0029] determining third nuclear magnetic coordinate information of the center position of the skin surface area in the nuclear magnetic coordinate system according to the second nuclear magnetic coordinate information and the nuclear magnetic image;

[0030] The first positional relationship information is determined according to the first nuclear magnetic coordinate information and the third nuclear magnetic coordinate information.

[0031] In some exemplary embodiments, determining the first position relationship information according to the first nuclear magnetic coordinate information and the third nuclear magnetic coordinate information includes:

[0032] Determine the first position relationship information as a difference between the first nuclear magnetic coordinate information and the third nuclear magnetic coordinate information;

[0033] Alternatively, determine the difference between the first nuclear magnetic coordinate information and the third nuclear magnetic coordinate information; determine the first position relationship information as the product of the difference and a third conversion relationship; wherein the third conversion relationship is the conversion relationship between the nuclear magnetic coordinate system and the device coordinate system.

[0034] In a second aspect, an embodiment of the present disclosure provides an electronic device, including:

[0035] at least one processor;

[0036] A memory, wherein at least one program is stored in the memory, and when the at least one program is executed by the at least one processor, the at least one processor implements any one of the above-mentioned methods for locating the target area.

[0037] In a third aspect, an embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, which implements any of the above-mentioned methods for locating a target area when executed by a processor.

[0038] The target area positioning method provided by the embodiment of the present disclosure realizes the intelligent recognition and intelligent positioning of the patient's lesion position during the surgical operation, improves the positioning accuracy of the patient's lesion position; and does not require the attachment of markers, thereby reducing the workload of medical staff. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The accompanying drawings are used to provide a further understanding of the embodiments of the present disclosure and constitute a part of the specification. Together with the embodiments of the present disclosure, they are used to explain the present disclosure and do not constitute a limitation of the present disclosure. Detailed exemplary embodiments are described with reference to the accompanying drawings, in which:

[0040] Figure 1 A flowchart of a method for locating a target area provided by one embodiment of the present disclosure;

[0041] Figure 2 Schematic diagram of conversion between the camera coordinate system and the image physical coordinate system according to an embodiment of the present disclosure;

[0042] Figure 3 A block diagram of a target area positioning device provided by another embodiment of the present disclosure. DETAILED DESCRIPTION

[0043] To enable those skilled in the art to better understand the technical solution of the present disclosure, the target area positioning method, electronic device, and computer-readable storage medium provided by the present disclosure are described in detail below with reference to the accompanying drawings.

[0044] Example embodiments will be described more fully hereinafter with reference to the accompanying drawings, but the example embodiments may be embodied in different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the scope of this disclosure to those skilled in the art.

[0045] In the absence of conflict, the various embodiments of the present disclosure and the various features therein may be combined with each other.

[0046] As used herein, the term "and / or" includes any and all combinations of at least one of the associated listed items.

[0047] The terms used herein are used only to describe specific embodiments and are not intended to limit the present disclosure. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms, unless the context clearly indicates otherwise. It will also be understood that when the terms "comprising" and / or "made of" are used in this specification, the presence of the features, wholes, steps, operations, elements, and / or components is specified, but the presence or addition of at least one other feature, whole, step, operation, element, component, and / or group thereof is not excluded.

[0048] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and the present disclosure, and will not be interpreted as having an idealized or overly formal meaning unless expressly defined as such herein.

[0049] Figure 1 A flowchart of a method for locating a target area provided by one embodiment of the present disclosure.

[0050] First, refer to Figure 1 An embodiment of the present disclosure provides a method for locating a target area, including:

[0051] Step 100: Capture a target image including a skin surface area corresponding to a reactive bone through a camera; wherein the reactive bone is a bone having target features.

[0052] In some exemplary embodiments, the camera may be any one of a monocular camera, a binocular camera, a multi-camera, and a 3D structured optical camera.

[0053] In some exemplary embodiments, the reactive bone may be a bone whose spatial positional relationship with the human skin surface does not change in a natural state, for example, the reactive bone may be the bridge of the nose, the sacrum, or the like.

[0054] In some exemplary embodiments, the skin surface area corresponding to the reactive bone refers to an area on the human skin surface that is located at the same location as the reactive bone but at a different depth. For example, if the reactive bone is the bridge of the nose, the skin surface area may be the area including the nose; if the reactive bone is the sacrum, the skin surface area may be the sacrococcygeal triangle.

[0055] Step 101: Identify the skin surface area from the target image.

[0056] In some exemplary embodiments, identifying the skin surface area from the target image includes: performing image enhancement processing on the target image; and inputting the target image after image enhancement processing into a trained classification model to obtain first pixel coordinate information of the skin surface area in the pixel coordinate system.

[0057] In some exemplary embodiments, identifying the skin surface area from the target image includes: inputting the target image into a trained classification model to obtain first pixel coordinate information of the skin surface area in a pixel coordinate system.

[0058] In some exemplary embodiments, the pixel coordinate system is a two-dimensional coordinate system established on the target image. The origin of the pixel coordinate system can be any point on the target image or any point on a non-target image, such as the upper left corner of the target image. One axis of the pixel coordinate system is parallel to the rows of the target image, and another axis is parallel to the columns of the target image. Alternatively, one axis of the pixel coordinate system is parallel to the columns of the target image, and another axis is parallel to the rows of the target image. The pixel coordinate information of a point on the target image in the pixel coordinate system is discrete, measured in pixels, and can only be integer values.

[0059] In some exemplary embodiments, since the brightness of the skin surface area in the target image is smaller than that of other surrounding areas, that is, it is darker, in order to enhance the image contrast of the skin surface area, prevent the excessive amplification of noise caused by the close grayscale of the image, and reduce the influence of light conditions on image features, the target image is enhanced. Specifically, the target image can be enhanced in a manner well known to those skilled in the art, for example, the target image can be enhanced using a contrast limited adaptive histogram equalization algorithm (CLAHE).

[0060] In some exemplary embodiments, before inputting the target image after image enhancement processing into the trained classification model to obtain the first pixel coordinate information of the skin surface area in the pixel coordinate system, or before inputting the target image into the trained classification model to obtain the first pixel coordinate information of the skin surface area in the pixel coordinate system, the method also includes: collecting a sample image including the skin surface area through a camera; performing image enhancement processing on the sample image; and performing model training based on the sample image after image enhancement processing to obtain a classification model.

[0061] In some exemplary embodiments, before inputting the target image after image enhancement processing into a trained classification model to obtain the first pixel coordinate information of the skin surface area in the pixel coordinate system, or before inputting the target image into a trained classification model to obtain the first pixel coordinate information of the skin surface area in the pixel coordinate system, the method also includes: collecting a sample image including the skin surface area through a camera; and performing model training based on the sample image to obtain a classification model.

[0062] In some exemplary embodiments, a classification model can be obtained by training using a model well known to those skilled in the art, for example, a Mask R-CNN neural network model can be used for training to obtain a classification model. Specifically, the implementation process of the Mask R-CNN neural network model generally includes: labeling the skin surface area of ​​a sample image or a sample image after image enhancement processing to generate a mask label data set; filtering and preprocessing the mask label data set, dividing the filtered and preprocessed data set to obtain a data set of different posture image combinations; inputting the data set of different posture image combinations into a pre-trained neural network (such as ResNet, etc.) to obtain a corresponding body surface feature map; for each point in the body surface feature map, a region of interest (ROI) is obtained according to the ROI; binary classification and regression (BB, Bounding-box regression) processing is performed on the candidate box to filter out a portion of points corresponding to low-scoring (lower score) ROIs; ROI alignment (Align) operation is performed on the remaining points in the candidate box, and the points after the ROI Align operation are classified.

[0063] Step 102: Determine first device coordinate information of the center position of the skin surface area in the device coordinate system.

[0064] In some exemplary embodiments, the device may be any device that performs a surgical procedure, such as a robotic arm.

[0065] In some exemplary embodiments, the device coordinate system is a three-dimensional coordinate system established based on the device.

[0066] In some exemplary embodiments, determining the first device coordinate information of the center position of the skin surface area in the device coordinate system includes: determining the second pixel coordinate information of the center position of the skin surface area in the pixel coordinate system; determining the camera coordinate information of the center position of the skin surface area in the camera coordinate system based on the second pixel coordinate information and the first conversion relationship; wherein the first conversion relationship is the conversion relationship between the pixel coordinate system and the camera coordinate system; determining the first device coordinate information based on the camera coordinate information and the second conversion relationship; wherein the second conversion relationship is the conversion relationship between the camera coordinate system and the device coordinate system.

[0067] In some exemplary embodiments, the camera coordinate system is a three-dimensional coordinate system established based on a camera.

[0068] In some exemplary embodiments, the first conversion relationship may be represented by a first conversion matrix.

[0069] In some exemplary embodiments, the camera coordinate system and the pixel coordinate system are associated through the image physical coordinate system, and the first conversion relationship can be obtained based on the conversion relationship between the camera coordinate system and the image physical coordinate system, and the conversion relationship between the image physical coordinate system and the pixel coordinate system.

[0070] In some exemplary embodiments, the conversion relationship between the camera coordinate system and the image physical coordinate system can be represented by a third conversion matrix, and the conversion relationship between the image physical coordinate system and the pixel coordinate system can be represented by a fourth conversion matrix. Then the first conversion matrix can be determined based on the third conversion matrix and the fourth conversion matrix.

[0071] In some exemplary embodiments, the image-physical coordinate system is a two-dimensional coordinate system established on the image sensor. The origin of the image-physical coordinate system is the intersection of the camera optical axis and the imaging plane. One axis of the image-physical coordinate system is parallel to the rows of the image sensor, and another axis is parallel to the columns of the image sensor. Alternatively, one axis of the image-physical coordinate system is parallel to the columns of the image sensor, and another axis is parallel to the rows of the image sensor. The image-physical coordinate information of a point on the image sensor in the image-physical coordinate system is discrete and measured in units of length.

[0072] In some exemplary embodiments, the camera coordinate system is a three-dimensional coordinate system, and the image physical coordinate system is a two-dimensional coordinate system. Therefore, the third transformation matrix is ​​a transformation matrix between the three-dimensional coordinate system and the two-dimensional coordinate system. Specifically, assuming that there is a point P on the skin surface area, the camera coordinate information of point P in the camera coordinate system is (Xc, Yc, Zc), and the intersection point Oc of the camera optical axis and the imaging plane and the line OcP connecting point P intersects with the camera imaging plane at point p, that is, the projection point of point P on the camera imaging plane, as shown in FIG. Figure 2As shown, the image physical coordinate information of point p in the image physical coordinate system is (x, y) and f is the focal length of the camera. Then, according to the principle of similar triangles, we can know that:

[0073]

[0074]

[0075] Then, the third transformation matrix can be expressed as:

[0076]

[0077] The fourth transformation matrix is ​​the transformation matrix between two two-dimensional coordinate systems, namely:

[0078]

[0079] Among them, α is the number of pixels contained in the unit length in the x direction, β is the number of pixels contained in the unit length in the y direction, (u, v) is the pixel coordinate information of point p, (x, y) is the physical image coordinate information of point p, and (u0, v0) is the pixel coordinate information of the origin of the image physical coordinate system in the pixel coordinate system.

[0080] Then, the first transformation matrix can be expressed as:

[0081]

[0082] Among them, K is the intrinsic parameter matrix of the camera, that is, the first transformation matrix.

[0083] In some exemplary embodiments, determining the camera coordinate information of the center position of the skin surface area in the camera coordinate system according to the second pixel coordinate information and the first conversion relationship includes: determining the camera coordinate information according to formula (4).

[0084] In some exemplary embodiments, the second conversion relationship may be represented by a second conversion matrix Le.

[0085] In some exemplary embodiments, the camera coordinate system and the device coordinate system are both three-dimensional coordinate systems. Therefore, the second transformation matrix is ​​the transformation matrix between the two three-dimensional coordinate systems. At the same time, the skin surface area only changes in spatial position and orientation in the two three-dimensional coordinate systems, and the shape does not change. Therefore, the second transformation matrix Le can be represented by a rotation matrix R and a translation matrix T. Specifically, assuming that there is a point P on the skin surface area, the camera coordinate information of point P in the camera coordinate system is (Xc, Yc, Zc), and the device coordinate information of point P in the device coordinate system is (Xe, Ye, Zee). The transformation relationship between the two coordinate information is expressed as shown in formula (5).

[0086]

[0087] Where R is a 3×3 matrix, T is the translation vector, Le is the external parameter matrix of the reaction camera in the device coordinate system.

[0088] In some exemplary embodiments, determining the first device coordinate information according to the camera coordinate information and the second conversion relationship includes: determining the first device coordinate information according to formula (5).

[0089] Step 103: Determine the second device coordinate information of the center position of the target area including the lesion in the device coordinate system based on the first device coordinate information and the predetermined first position relationship information; wherein the first position relationship information is the position relationship information between the center position of the skin surface area and the center position of the target area.

[0090] In some exemplary embodiments, the lesion may be a tumor, such as uterine fibroids.

[0091] In some exemplary embodiments, the first position relationship information is the difference between the first device coordinate information and the fourth device coordinate information of the center position of the target area in the device coordinate system; determining the second device coordinate information of the center position of the target area including the lesion in the device coordinate system based on the first device coordinate information and the predetermined first position relationship information includes: determining the second device coordinate information as the difference between the first device coordinate information and the first position relationship information.

[0092] In some exemplary embodiments, the first position relationship information is the difference between the third nuclear magnetic coordinate information of the center position of the skin surface area in the nuclear magnetic coordinate system and the first nuclear magnetic coordinate information of the center position of the target area in the nuclear magnetic coordinate system; determining the second device coordinate information of the center position of the target area including the lesion in the device coordinate system according to the first device coordinate information and the predetermined first position relationship information includes: determining the difference between the first device coordinate information and the fourth device coordinate information according to the third conversion relationship, the difference between the third nuclear magnetic coordinate information and the first nuclear magnetic coordinate information; determining the second device coordinate information as the difference between the first device coordinate information and the difference between the first device coordinate information and the fourth device coordinate information.

[0093] In some exemplary embodiments, the third transformation relationship is the transformation relationship between two three-dimensional coordinate systems, the nuclear magnetic coordinate system and the device coordinate system. The third transformation relationship can be represented by the fifth transformation matrix. The third transformation matrix is ​​similar to the second transformation matrix Le and will not be repeated here.

[0094] In some exemplary embodiments, before capturing the target image including the skin surface area corresponding to the reaction bone through the camera, the method further includes: obtaining first position relationship information based on the nuclear magnetic resonance image in advance.

[0095] In some exemplary embodiments, obtaining the first positional relationship information in advance based on the nuclear magnetic image includes: determining first nuclear magnetic coordinate information of the center position of the target area in the nuclear magnetic coordinate system based on the nuclear magnetic image, and second nuclear magnetic coordinate information of the target position of the bone in the nuclear magnetic coordinate system; determining third nuclear magnetic coordinate information of the center position of the skin surface area in the nuclear magnetic coordinate system based on the second nuclear magnetic coordinate information and the nuclear magnetic image; and determining the first positional relationship information based on the first nuclear magnetic coordinate information and the third nuclear magnetic coordinate information.

[0096] In some exemplary embodiments, the target location of the reactive bone may be the sacrococcygeal junction.

[0097] In some exemplary embodiments, the center of the skin surface area is at a different depth but at the same location as the sacrum and coccyx, alternating therewith.

[0098] In some exemplary embodiments, determining the first position relationship information based on the first nuclear magnetic coordinate information and the third nuclear magnetic coordinate information includes: determining the first position relationship information as the difference between the first nuclear magnetic coordinate information and the third nuclear magnetic coordinate information; or, determining the difference between the first nuclear magnetic coordinate information and the third nuclear magnetic coordinate information; determining the first position relationship information as the product of the difference and a third conversion relationship; wherein the third conversion relationship is a conversion relationship between the nuclear magnetic coordinate system and the device coordinate system.

[0099] The target area positioning method provided by the embodiment of the present disclosure realizes the intelligent recognition and intelligent positioning of the patient's lesion position during the surgical operation, improves the positioning accuracy of the patient's lesion position; and does not require the attachment of markers, thereby reducing the workload of medical staff.

[0100] In a second aspect, another embodiment of the present disclosure provides an electronic device, including:

[0101] at least one processor;

[0102] A memory stores at least one program, and when the at least one program is executed by at least one processor, the at least one processor implements any one of the above-mentioned methods for locating a target area.

[0103] Among them, the processor is a device with data processing capabilities, including but not limited to the central processing unit (CPU); the memory is a device with data storage capabilities, including but not limited to random access memory (RAM, more specifically SDRAM, DDR, etc.), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), and flash memory (FLASH).

[0104] In some exemplary embodiments, the processor and the memory are connected to each other through a bus, and further connected to other components of the computing device.

[0105] In some exemplary embodiments, the electronic device further comprises: a camera for acquiring a target image including a skin surface area corresponding to a reactive bone; wherein the reactive bone is a bone having a target feature.

[0106] In a third aspect, another embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, which implements any of the above-mentioned methods for locating a target area when the program is executed by a processor.

[0107] Figure 3 A block diagram of a target area positioning device provided by another embodiment of the present disclosure.

[0108] In a fourth aspect, another embodiment of the present disclosure provides a device for positioning a target area, including: an acquisition module 301, for collecting a target image including a skin surface area corresponding to a reaction bone through a camera; wherein the reaction bone is a bone with target features; an identification module 302, for identifying the skin surface area from the target image; a coordinate information determination module 303, for determining first device coordinate information of a center position of the skin surface area in a device coordinate system; and determining second device coordinate information of a center position of a target area including a lesion in the device coordinate system based on the first device coordinate information and a predetermined first position relationship information; wherein the first position relationship information is the position relationship information between the center position of the skin surface area and the center position of the target area.

[0109] In some exemplary embodiments, the recognition module 302 is specifically used to: perform image enhancement processing on the target image; input the target image after image enhancement processing into a trained classification model to obtain the first pixel coordinate information of the skin surface area in the pixel coordinate system.

[0110] In some exemplary embodiments, the acquisition module 301 is further used to: collect a sample image including the skin surface area through the camera; the recognition module 302 is further used to: perform image enhancement processing on the sample image; and perform model training based on the sample image after image enhancement processing to obtain the classification model.

[0111] In some exemplary embodiments, the coordinate information determination module 303 is specifically used to implement the determination of the first device coordinate information of the center position of the skin surface area in the device coordinate system in the following manner: determine the second pixel coordinate information of the center position of the skin surface area in the pixel coordinate system; determine the camera coordinate information of the center position of the skin surface area in the camera coordinate system based on the second pixel coordinate information and the first conversion relationship; wherein the first conversion relationship is the conversion relationship between the pixel coordinate system and the camera coordinate system; determine the first device coordinate information based on the camera coordinate information and the second conversion relationship; wherein the second conversion relationship is the conversion relationship between the camera coordinate system and the device coordinate system.

[0112] In some exemplary embodiments, the first position relationship information is the difference between the first device coordinate information and the fourth device coordinate information of the center position of the target area in the device coordinate system; the coordinate information determination module 303 is specifically used to implement the second device coordinate information of the center position of the target area including the lesion in the device coordinate system based on the first device coordinate information and the predetermined first position relationship information in the following manner: determine the second device coordinate information as the difference between the first device coordinate information and the first position relationship information.

[0113] In some exemplary embodiments, the acquisition module 301 is further configured to: acquire the first position relationship information in advance based on a nuclear magnetic resonance image.

[0114] In some exemplary embodiments, the acquisition module 301 is specifically used to implement the acquisition of the first position relationship information in advance based on the nuclear magnetic image in the following manner: determine the first nuclear magnetic coordinate information of the center position of the target area in the nuclear magnetic coordinate system and the second nuclear magnetic coordinate information of the target position of the reaction bone in the nuclear magnetic coordinate system based on the nuclear magnetic image; determine the third nuclear magnetic coordinate information of the center position of the skin surface area in the nuclear magnetic coordinate system based on the second nuclear magnetic coordinate information and the nuclear magnetic image; determine the first position relationship information based on the first nuclear magnetic coordinate information and the third nuclear magnetic coordinate information.

[0115] In some exemplary embodiments, the acquisition module 301 is specifically used to implement the determination of the first position relationship information based on the first nuclear magnetic coordinate information and the third nuclear magnetic coordinate information in the following manner: determining the first position relationship information as the difference between the first nuclear magnetic coordinate information and the third nuclear magnetic coordinate information; or determining the difference between the first nuclear magnetic coordinate information and the third nuclear magnetic coordinate information; determining the first position relationship information as the product of the difference and a third conversion relationship; wherein the third conversion relationship is the conversion relationship between the nuclear magnetic coordinate system and the device coordinate system.

[0116] The specific implementation process of the above-mentioned target area positioning device is the same as the specific implementation process of the target area positioning method in the above-mentioned embodiment, and will not be repeated here.

[0117] It will be appreciated by those skilled in the art that all or some of the steps, systems, and functional modules / units in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. In hardware implementations, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed by several physical components in cooperation. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transitory medium) and a communication medium (or temporary medium). As is well known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable, and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, as is well known to those skilled in the art, communication media typically embodies computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0118] Example embodiments have been disclosed herein, and although specific terms are employed, they are used and should be interpreted only in a general illustrative sense and not for purposes of limitation. In some instances, it will be apparent to those skilled in the art that, unless otherwise expressly indicated, features, characteristics, and / or elements described in conjunction with a particular embodiment may be used alone or in combination with features, characteristics, and / or elements described in conjunction with other embodiments. Therefore, it will be understood by those skilled in the art that various changes in form and detail may be made without departing from the scope of the present disclosure as set forth in the appended claims.

Claims

1. A method for locating a target area, comprising: A target image including a skin surface area corresponding to a reactive bone is captured by a camera; wherein the reactive bone is a bone having target features and whose spatial positional relationship with the human skin surface does not change in a natural state; identifying the skin surface area from the target image; Determine first device coordinate information of a center position of the skin surface area in a device coordinate system; determining second device coordinate information of the center position of the target area including the lesion in the device coordinate system based on the first device coordinate information and predetermined first position relationship information; wherein the first position relationship information is position relationship information between the center position of the skin surface area and the center position of the target area; Before acquiring the target image including the skin surface area corresponding to the reactive bone by the camera, the method further includes: Determining first nuclear magnetic coordinate information of the center position of the target area in the nuclear magnetic coordinate system and second nuclear magnetic coordinate information of the target position of the reaction bone in the nuclear magnetic coordinate system according to the nuclear magnetic image; determining third nuclear magnetic coordinate information of the center position of the skin surface area in the nuclear magnetic coordinate system according to the second nuclear magnetic coordinate information and the nuclear magnetic image; The first positional relationship information is determined according to the first nuclear magnetic coordinate information and the third nuclear magnetic coordinate information.

2. The method for locating a target area according to claim 1, wherein: The identifying the skin surface area from the target image includes: performing image enhancement processing on the target image; The target image after image enhancement processing is input into the trained classification model to obtain the first pixel coordinate information of the skin surface area in the pixel coordinate system.

3. The target area positioning method according to claim 2, wherein before inputting the enhanced target image into a trained classification model to obtain first pixel coordinate information of the skin surface area in a pixel coordinate system, the method further comprises: collecting a sample image including the skin surface area by the camera; performing image enhancement processing on the sample image; The classification model is obtained by performing model training based on the sample images after image enhancement processing.

4. The method for locating a target area according to claim 1, wherein: The determining of the first device coordinate information of the center position of the skin surface area in the device coordinate system includes: Determining second pixel coordinate information of the center position of the skin surface area in a pixel coordinate system; Determining camera coordinate information of the center position of the skin surface area in a camera coordinate system according to the second pixel coordinate information and a first conversion relationship; wherein the first conversion relationship is a conversion relationship between the pixel coordinate system and the camera coordinate system; The first device coordinate information is determined according to the camera coordinate information and a second conversion relationship; wherein the second conversion relationship is a conversion relationship between the camera coordinate system and the device coordinate system.

5. The method for locating a target area according to claim 1, wherein: The first position relationship information is a difference between the first device coordinate information and fourth device coordinate information of the center position of the target area in the device coordinate system; The second device coordinate information of the center position of the target area including the lesion in the device coordinate system determined according to the first device coordinate information and the predetermined first position relationship information includes: The second device coordinate information is determined to be a difference between the first device coordinate information and the first position relationship information.

6. The method for locating a target area according to claim 1, wherein: Determining the first position relationship information according to the first nuclear magnetic coordinate information and the third nuclear magnetic coordinate information includes: Determine the first position relationship information as a difference between the first nuclear magnetic coordinate information and the third nuclear magnetic coordinate information; Alternatively, determine the difference between the first nuclear magnetic coordinate information and the third nuclear magnetic coordinate information; determine the first position relationship information as the product of the difference and a third conversion relationship; wherein the third conversion relationship is the conversion relationship between the nuclear magnetic coordinate system and the device coordinate system.

7. An electronic device comprising: at least one processor; A memory having at least one program stored thereon, wherein when the at least one program is executed by the at least one processor, the at least one processor implements the method for locating a target area according to any one of claims 1 to 6.

8. A computer-readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the method for locating a target area according to any one of claims 1 to 6 is implemented.

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