Method, device, electronic equipment and medical system for generating medical image data

Abstract

The application provides a medical image data generation method, device, electronic equipment and medical system. The medical image data generation method comprises: acquiring first image data, which is obtained from image data of a target object collected by a first image device; determining a first reference object of a preset region of the target object according to the first image data; determining rotation data according to a positional relationship between the first reference object and a second reference object of a support surface of a second image device, the second image device being an image device matched with an interventional robot; determining offset data according to a distance between a first preset position of the preset region and a second preset position of the support surface; and determining second image data of the target object under the second image device according to the first image data, the rotation data and the offset data, so that the feasibility of preoperative planning under the image device matched with the interventional robot can be determined in the case of acquiring the first image data.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of image processing, and particularly relates to a medical image data generation method and device, an electronic device, and a medical system. BACKGROUND

[0002] Computed Tomography (CT) and Magnetic Resonance (MR) image data are important basis for medical diagnosis and are also data required for surgery or surgery planning by an interventional robot. For example, it is necessary to determine in advance whether the interventional robot can move within a fixed aperture during surgery according to image data.

[0003] Generally, surgery planning can be performed according to specific image data under a CT matched with the interventional robot, and then the feasibility of a surgery plan can be determined. However, in some scenarios, it is inconvenient to obtain specific image data of a human body under a CT matched with the interventional robot, and in this case, only image data of the human body collected by a third-party image device can be used. However, if preoperative planning is performed based on third-party image data, the feasibility of the preoperative planning under a CT matched with the interventional robot cannot be determined. SUMMARY

[0004] Therefore, embodiments of the present application provide a medical image data generation method and device, an electronic device, and a medical system, which can determine the feasibility of surgery on an image device matched with an interventional robot according to image data of a target object under a third-party image device.

[0005] A first aspect of embodiments of the present application provides a method for generating image data, comprising:

[0006] obtaining first image data, wherein the first image data is obtained from image data of a target object collected by a first image device;

[0007] determining a first reference object of a preset region of the target object according to the first image data;

[0008] determining rotation data of the preset region according to a positional relationship between the first reference object and a second reference object of a second image device, wherein the second image device is an image device matched with an interventional robot, and the second reference object is a symmetrical face or a symmetrical axis of a support face of the second image device;

[0009] determining offset data according to a distance between a first preset position of the preset region and a second preset position of the support face;

[0010] According to the first image data, the rotation data and the offset data, second image data of the target object under the second imaging device is determined.

[0011] In an embodiment, the first reference object of the preset region in the target object is determined according to the first image data, comprising:

[0012] An image of the preset region is determined according to the first image data;

[0013] A similarity between an image of the preset region after rotation around each candidate object and the image of the preset region is determined, wherein the candidate object is obtained according to a preset algorithm;

[0014] The candidate object corresponding to the maximum similarity is taken as the first reference object.

[0015] In an embodiment, the first reference object of the preset region in the target object is determined according to the first image data, comprising:

[0016] Image data of a preset part of the preset region is determined according to the first image data, wherein the preset part includes any one or more of an outer wall of the preset region, a bone in the preset region, and an organ in the preset region satisfying a preset shape;

[0017] The first reference object of the preset region is determined according to the image data of the preset part.

[0018] In an embodiment, the offset data is determined according to a distance between a first preset position of the preset region and a second preset position of the support surface, comprising:

[0019] After rotating the preset region according to the rotation data, the preset region is moved, and when the distance between the first preset position and the second preset position is less than a first preset distance, a movement distance of the preset region is taken as a first offset;

[0020] The preset region is moved on the second reference object, and when a nearest distance between the preset region and the support surface is less than a second preset distance, a second offset of the preset region is determined;

[0021] The offset data is determined according to the first offset and the second offset.

[0022] In an embodiment, the preset region is moved, comprising:

[0023] The preset region is moved according to a positional relationship between point cloud data of the preset region and point cloud data of the support surface.

[0024] In an embodiment, the acquiring the first image data comprises:

[0025] acquiring raw image data obtained by the first image device scanning the target object;

[0026] determining position conversion data according to a first position of the target object when the first image device scans the target object and a second position corresponding to the second image device;

[0027] determining the first image data according to the raw image data and the position conversion data.

[0028] In an embodiment, the determining the first image data according to the raw image data and the position conversion data comprises:

[0029] scaling an image corresponding to the raw image data according to a device parameter of the first image device when the first image device scans the target object and a device parameter of the second image device, to obtain scaled image data;

[0030] determining the first image data according to the scaled image data and the position conversion data.

[0031] A second aspect of the embodiment of the present application provides a medical image data generation device, comprising:

[0032] an acquisition module configured to acquire first image data, the first image data being obtained by image data of a target object collected by a first image device;

[0033] a symmetry surface determination module configured to determine a first reference object of a preset region of the target object according to the first image data;

[0034] a rotation data determination module configured to determine rotation data of the preset region according to a positional relationship between the first reference object and a second reference object of a second image device, the second image device being an image device matched with an interventional robot, and the second reference object being a symmetry surface or a symmetry axis of a support surface of the second image device;

[0035] an offset data determination module configured to determine offset data according to a distance between a first preset position of the preset region and a second preset position of the support surface;

[0036] a conversion module configured to determine second image data of the target object under the second image device according to the first image data, the rotation data and the offset data.

[0037] A third aspect of the embodiments of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the medical image data generation method according to the first aspect.

[0038] A fourth aspect of the embodiments of the present application provides a medical system, including a robot, a path planning device, and the electronic device according to the third aspect, and the path planning device is configured to plan a path of the robot according to the second image data.

[0039] A fifth aspect of the embodiments of the present application provides a computer readable storage medium, and the computer readable storage medium stores a computer program, and the computer program is executable on a processor to implement the medical image data generation method according to the first aspect.

[0040] A sixth aspect of the embodiments of the present application provides a computer program product, and when the computer program product is executed on an electronic device, the electronic device is caused to execute the medical image data generation method according to any one of the first aspect.

[0041] Compared with the prior art, the embodiments of the present application have the beneficial effects that: by acquiring first image data of a target object under a first image device, determining a first reference object of a preset region of the target object according to the first image data, further determining rotation data of the preset region according to a position relationship between the first reference object and a second reference object of a support surface of a second image device, determining offset data according to a distance between a first preset position of the preset region and a second preset position of a bed plate, and finally determining second image data of the target object under the second image device according to the first image data, the rotation data and the offset data, since the second image device is matched with an interventional robot, preoperative planning can be performed based on the second image data, and the feasibility of the preoperative planning can be determined, that is, the feasibility of the preoperative planning under the second image device matched with the interventional robot can be determined even if only the first image data is acquired. BRIEF DESCRIPTION OF DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiments or prior art description will be briefly introduced as follows.

[0043] Figure 1 is an implementation flow diagram of the image data generation method provided by an embodiment of the present application;

[0044] Figure 2 is a schematic diagram of a human body region provided by an embodiment of the present application;

[0045] Figure 3is a schematic diagram of a first symmetry plane provided by an embodiment of the present application;

[0046] Figure 4 is a schematic diagram of an abdominal wall of an abdominal cavity provided by an embodiment of the present application;

[0047] Figure 5 is a schematic diagram of a second symmetry plane provided by an embodiment of the present application;

[0048] Figure 6 is a schematic diagram of a human body region in a righted state provided by an embodiment of the present application;

[0049] Figure 7 is a schematic diagram of moving a human body region according to a first preset position and a second preset position provided by an embodiment of the present application;

[0050] Figure 8 is a schematic diagram of moving a human body region in a vertical direction of a bed board provided by an embodiment of the present application;

[0051] Figure 9 is a schematic diagram of second image data provided by an embodiment of the present application;

[0052] Figure 10 is a schematic diagram of a medical system provided by an embodiment of the present application;

[0053] Figure 11 is a schematic diagram of a generation apparatus of image data provided by an embodiment of the present application;

[0054] Figure 12 is a schematic diagram of a structure of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0055] In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular sequences of steps, techniques, etc., in order to provide a thorough understanding of the present embodiments. However, it will be apparent to those skilled in the art that the present embodiments can be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known methods, devices, and circuits are omitted so as not to obscure the description of the present embodiments.

[0056] It should be understood that the term "comprising" when used in this specification and the appended claims, specifies the presence of stated features, integers, steps, operations, elements, and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0057] It should also be understood that the term “and / or” as used herein refers to any one of the associated listed items, or a combination of any and all of the associated listed items, and includes these combinations.

[0058] As used in the specification and the appended claims, the term “if’ can be interpreted as meaning “when” or “once” or “in response to a determination” or “in response to detecting” depending on the context. Similarly, the phrase “if it is determined” or “if [the recited condition or event] is detected” can be interpreted as meaning “once it is determined” or “in response to a determination” or “once [the recited condition or event] is detected” or “in response to detecting [the recited condition or event]” depending on the context.

[0059] In addition, in the description of the present application, the terms “first”, “second”, etc. are only used for differentiation in description, and cannot be understood as indicating or implying relative importance.

[0060] In the prior art, before surgical planning is performed, there is a problem that the image data of a target object collected by an image device matched with an interventional robot cannot be obtained, and only third-party image data collected by a third-party image device can be obtained. Since the bed height, aperture size, body position when collecting data, and other factors of the third-party image device and the image device matched with the interventional robot are inconsistent, if preoperative planning is performed according to the third-party image data, the feasibility of the preoperative planning under the image device matched with the interventional robot cannot be judged.

[0061] Therefore, the present application provides an image data generation method. The image data generation method includes the following steps: acquiring first image data of a target object under a first image device; determining a first reference object of a preset region of the target object according to the first image data; determining rotation data of the preset region according to an included angle between the first reference object and a second reference object of a support surface of a second image device; determining offset data according to a distance between a first preset position of the preset region and a second preset position of the support surface; and determining second image data of the target object under the second image device according to the first image data, the rotation data, and the offset data. Thus, the second image data under the image device matched with the interventional robot can be obtained, which facilitates subsequent preoperative planning based on the second image data and determines the feasibility of the preoperative planning. Therefore, the feasibility of the preoperative planning under the second image device matched with the interventional robot can also be judged in the case of only acquiring the first image data.

[0062] The image data generation method provided by the present application will be described below. The image data generation method provided by the present application can be executed by an electronic device. The electronic device can be a computing device in communication with the first image device and the second image device.

[0063] As an example, the embodiment of the present application provides a scene including an electronic device and a first imaging device, wherein the electronic device is configured to execute the method for generating imaging data provided by the embodiment of the present application, and the first imaging device is configured to provide first imaging data to the electronic device. As an example, the electronic device and the first imaging device have a communication connection. Thus, the electronic device and the first imaging device can transmit data, such as the first imaging data, through the communication connection. Of course, the first imaging data can also be input by a user into the electronic device or downloaded by the electronic device from other third-party devices (such as a cloud server), and the embodiment of the present application does not limit this.

[0064] Please refer to the accompanying Figure 1 The method for generating imaging data provided by an embodiment of the present application includes the following steps.

[0065] S101: The electronic device acquires first imaging data. For example, the first imaging data is obtained from imaging data of a target object collected by a first imaging device.

[0066] The target object can be a human body, an animal, or the like. The first imaging device is a third-party imaging device and is not matched with the interventional robot. The first imaging device can be a CT, an MR, or a positron emission tomography (PET)-CT, and the first imaging data can be point cloud data of the target object or an image of the target object. The point cloud data and the image can be converted into each other.

[0067] In an embodiment, the first imaging data acquired by the electronic device can be original imaging data obtained by the first imaging device by scanning the target object, or can be imaging data obtained by the first imaging device by processing the original imaging data.

[0068] In the embodiment of the present application, the electronic device can acquire the first imaging data from the first imaging device, or can acquire the first imaging data collected by the first imaging device from other devices.

[0069] In another embodiment, the electronic device acquires original imaging data from the first imaging device, and processes the original imaging data by data conversion, scaling, or the like to obtain the first imaging data.

[0070] S102: The electronic device determines a first reference object of a preset region of the target object according to the first imaging data.

[0071] The first image data can be image data of a three-dimensional image or image data of a two-dimensional image. The preset region is a region selected from the target object, and the preset region can have an approximately symmetrical structure. The image of the preset region can be a three-dimensional image or a two-dimensional image. If the image of the preset region is a three-dimensional image, the first reference object is approximately a symmetrical surface of the preset region. If the image of the preset region is a two-dimensional image, the first reference object is approximately a symmetrical axis of the preset region. For example, the target object is a human body, and the preset region can be a chest, an abdomen, or a head of the human body.

[0072] In S103, the electronic device determines rotation data of the preset region according to a positional relationship between the first reference object and a second reference object of a second image device. The second image device is an image device matched with the interventional robot, and the second reference object is a symmetrical surface or a symmetrical axis of a support surface of the second image device.

[0073] The support surface can be a bed plate or a plane for placing an object to be collected. If the image of the preset region is a three-dimensional image, the second reference object is a symmetrical surface of the support surface. If the image of the preset region is a two-dimensional image, the second reference object is a symmetrical axis of the support surface. When the first reference object and the second reference object satisfy a set positional relationship, the target object is in a correct position on the support surface.

[0074] In S104, the electronic device determines offset data according to a distance between a first preset position of the preset region and a second preset position of the support surface.

[0075] The first preset position and the second preset position can be a center point, a vertex, or a specified corresponding point of the preset region and the support surface, respectively. The preset region is offset according to the first preset position and the second preset position, so that the preset region is located at a specified position on the support surface, for example, at a central region of the support surface.

[0076] In S105, the electronic device determines second image data of the target object under the second image device according to the first image data, the rotation data, and the offset data.

[0077] The rotation data represents an angle of rotation of the preset region when the preset region is in a correct position on the support surface. The offset data represents a distance of movement of the preset region when the preset region is located at a specified position on the support surface. The rotation angle and the movement distance of the preset region are consistent with the rotation angle and the movement distance of the target object. Therefore, the electronic device transforms the first image data according to the rotation data and the offset data, and obtains the second image data.

[0078] Exemplarily, the rotation data and the offset data can be represented by matrices, the rotation data and the offset data are multiplied to obtain a conversion matrix, and the first image data is converted according to the conversion matrix to obtain the second image data of the target object under the second image device.

[0079] In the above embodiment, by obtaining the first image data of the target object under the first image device, the first reference object of the preset region of the target object is determined according to the first image data, the rotation data of the preset region is determined according to the included angle between the first reference object and the second reference object of the support surface of the second image device, the offset data is determined according to the distance between the first preset position of the preset region and the second preset position of the support surface, and finally the second image data of the target object under the second image device is determined according to the first image data, the rotation data and the offset data, so that the second image data under the image device matched with the interventional robot can be obtained, and the subsequent preoperative planning based on the second image data is facilitated, and the feasibility of the preoperative planning is determined. Therefore, in the case of only obtaining the first image data, the feasibility of the preoperative planning under the second image device matched with the interventional robot can also be determined.

[0080] In an embodiment, after the electronic device obtains the original image data obtained by the first image device scanning the target object, the electronic device determines the body position conversion data according to the first body position when the first image device scans the target object and the second body position corresponding to the second image device, and determines the first image data according to the original image data and the body position conversion data. The first body position and the second body position can refer to the placement manner of the target object on the support surface of the image device. The second body position can be determined according to the body position required when the target object is operated, and can be set by the user or matched by the electronic device according to the device information of the second image device and the operation requirement.

[0081] Exemplarily, when the image device scans the human body, the body position of the human body can generally be any one of the following body positions: head first supine (HFS), feet first supine (FFS), head first prone (HFP), feet first prone (FFP), head first decubitus left (HFDL), feet first decubitus left (FFDL), head first decubitus right (HFDR), and feet first decubitus right (HFDR).

[0082] When the first imaging device scans the human body, the human body can be in any position, and the position of the human body when the second imaging device scans the human body must be the position required by the interventional robot during surgery. If the position of the human body when the first imaging device scans the human body is the same as the position of the human body when the second imaging device scans the human body, the original image data collected by the first imaging device can be used as the first image data for subsequent processing. If the first position of the human body when the first imaging device scans the human body is different from the second position of the human body when the second imaging device scans the human body, the original image data needs to be converted in position to obtain the first image data in the second position. The second position of the human body when the second imaging device scans the human body is the position of the human body required by the interventional robot during surgery. For example, if the first position of the human body when the first imaging device scans the human body is the HFS position, and the position required by the interventional robot during surgery is the HFDL position, the image data collected by the first imaging device needs to be converted in position.

[0083] In an embodiment, after the electronic device obtains the original image data, the electronic device determines the conversion data according to the first position of the human body when the first imaging device scans the human body and the second position corresponding to the second imaging device, and then determines the first image data according to the original image data and the conversion data.

[0084] Exemplarily, different positions of the human body can be represented by different matrices. For example,

[0085] The matrix corresponding to the HFS position is

[0086] The matrix corresponding to the FFS position is

[0087] The matrix corresponding to the HFP position is

[0088] The matrix corresponding to the FFP position is

[0089] The matrix corresponding to the HFDL position is

[0090] The matrix corresponding to the FFDL position is

[0091] The matrix corresponding to the HFDR position is

[0092] The matrix corresponding to the FFDL position is

[0093] The electronic device can determine the conversion data according to the matrices corresponding to the first position and the second position, the conversion data can be represented by a matrix, and the first image data after position conversion can be determined according to the conversion data.

[0094] In an embodiment, after obtaining the original image data of the target object, the electronic device first determines a first conversion matrix between the first body position and the third body position, and determines the image data under the third body position according to the first conversion matrix. Then, the electronic device determines a second conversion matrix between the third body position and the second body position, and determines the first image data under the second body position according to the second conversion matrix, so as to reduce the computational complexity.

[0095] Exemplarily, the third body position is the HFS body position. For any point P(x, y, z) on the original image data of the human body, a conversion matrix M1 between the first body position and the HFS body position is determined, P1=M1*P is obtained, P1 represents a point corresponding to P in the image data under the HFS body position, so as to convert the original image data under the first body position into the image data under the HFS body position. Then, a conversion matrix M2 between the HFS body position and the second body position is determined, P2=M2*P1 is obtained, P2 represents a point corresponding to P1 in the first image data under the second body position, so as to convert the image data under the HFS body position into the first image data.

[0096] For example, the first body position is the FFS body position, and the second body position is the HFP body position, then,

[0097]

[0098] According to the original image data and the above two conversion matrices, the first image data under the second body position can be obtained.

[0099] In the above embodiment, the original image data is converted by the body position conversion data, the first image data matched with the second image device can be obtained, so that the target object body position when the first image device is scanned is not limited when the surgical planning is performed, and the application range of the interventional robot for surgical planning is expanded.

[0100] In an embodiment, in the case that the first body position of the first image data is consistent with the second body position corresponding to the second image device, the first image data is converted according to the rotation data and the offset data, so as to obtain the second image data of the target object under the second image device, thereby realizing the alignment operation of the first image data and the support surface of the second image device. In the case that the first body position of the first image data is inconsistent with the second body position corresponding to the second image device, the first image data is converted according to the body position conversion matrix, the rotation data and the offset data, so as to obtain the second image data of the target object under the second image device.

[0101] In an embodiment, after the electronic device obtains the original image data, the electronic device scales the image corresponding to the original image data according to the device parameter when the first image device scans the target object and the device parameter of the second image device, to obtain a scaled image, and then determines the scaled image data according to the scaled image, the size of the scaled image is consistent with the device parameter of the second image device scanning the target object, and the device parameter can refer to a scaling factor, a resolution, and the like. After the electronic device obtains the scaled image data, the electronic device performs a body position conversion on the scaled image data according to the scaled image data and the body position conversion data, to obtain the first image data, so as to obtain the first image data matched with the second image device, and to improve the subsequent calculation accuracy.

[0102] In an embodiment, the method for determining the first reference object of the target object is as follows: determining the image of the preset region according to the first image data, determining the similarity of the image of the preset region after the image of the preset region is rotated around each candidate object, and the candidate object is obtained according to a preset algorithm; and taking the candidate object corresponding to the maximum similarity as the first reference object.

[0103] Specifically, if the image of the preset region is a three-dimensional image, the first reference object is a first reference surface, the image of the preset region is sequentially rotated around each candidate symmetry surface, the similarity of all the rotated images and the image of the preset region is calculated, and the candidate symmetry surface corresponding to the maximum similarity is taken as the first reference surface, and the first reference surface is close to the symmetry surface of the preset region.

[0104] If the image of the preset region is a two-dimensional image, the first reference object is a first reference line, the image of the preset region is sequentially rotated around each candidate symmetry axis, the similarity of all the rotated images and the image of the preset region is calculated, and the candidate symmetry axis corresponding to the maximum similarity is taken as the first reference line, and the first reference surface is close to the symmetry axis of the preset region.

[0105] Exemplarily, the preset region is the head, chest, or abdomen of a human body, and the head, chest, or abdomen of the human body can also be referred to as a human body region. Figure 2 The schematic diagram is for the abdomen of the human body, and the human body region is generally approximately a symmetric structure, so the first reference surface close to the symmetry surface of the human body region can be determined, and the first reference line close to the symmetry axis of the cross section of the human body region can be determined.

[0106] In the following, the target object is taken as a human body, and the preset region is taken as a human body region as an example to describe the determination of the first reference object of the target object. The image of the preset region is a three-dimensional image, and the first reference object is a first reference surface.

[0107] The electronic device identifies a human body region by using a deep learning algorithm after obtaining the first image data, so as to determine the image of the human body region. Alternatively, the first image data is a human body image, and the electronic device determines a human body region mask by using an image segmentation algorithm, and segments the image of the human body region from the human body image according to the human body region mask. For example, the electronic device can segment the image of the human body region from the first image data by using any one of a threshold-based segmentation algorithm, an edge detection-based segmentation algorithm, a clustering-based segmentation algorithm, a region-based segmentation algorithm, and the like.

[0108] In an embodiment, as shown in FIG. 3, after the electronic device obtains the image of the human body region, the electronic device determines a candidate symmetry plane 31 according to a preset algorithm, and then determines the similarity between the image of the human body region and the image of the human body region rotated around the candidate symmetry plane, so as to determine the first reference plane close to the symmetry plane according to the similarity. Figure 3 The preset algorithm can be a target optimization algorithm, such as a gradient descent algorithm, a genetic algorithm, and the like.

[0109] Specifically, the electronic device first randomly generates a candidate symmetry plane, or determines a candidate symmetry plane passing through the center point of the human body region according to the length or shape of the human body region. Then, the electronic device calculates the similarity between the image of the human body region and the image of the human body region rotated 180° around the candidate symmetry plane. Then, the electronic device determines the next candidate symmetry plane according to the similarity and the target optimization algorithm, so that the similarity corresponding to the next candidate symmetry plane is larger, or the electronic device generates the next candidate symmetry plane according to a preset angle interval, and calculates the similarity between the image of the human body region and the image of the human body region rotated 180° around the next candidate symmetry plane. In this way, the process is repeated until the maximum similarity is obtained, and the candidate symmetry plane corresponding to the maximum similarity is the first reference plane. Since the human body region is approximately left-right symmetric, the image of the human body region rotated 180° around the symmetry plane has structural similarity with the image of the human body region. Therefore, the candidate symmetry plane corresponding to the maximum similarity is the first reference plane, and the first reference plane is close to the left-right symmetry plane of the human body.

[0110] For example, the process of determining the first reference plane is regarded as an optimization problem of a target function, and the target function is u(f) = min(f-D(f)), where f represents the image of the human body region, D(f) represents the image of the human body region rotated around the candidate symmetry plane, and u(f) represents the rotation vector of the candidate symmetry plane corresponding to the minimum difference (maximum similarity) between the image of the human body region and the image of the human body region rotated around the candidate symmetry plane, that is, the rotation vector of the first reference plane. The rotation vector of the first reference plane is the rotation vector of the first reference plane in a set coordinate system.

[0111] In another embodiment, the electronic device may also use the plane containing the midline of the human body region as the first reference plane. For example, the electronic device may also determine the midlines of multiple cross-sections of the human body region based on its length or shape, and the plane composed of the multiple centers shall be the first reference plane.

[0112] In one embodiment, the target object is a human body, and the preset area is a human body area. The electronic device can first determine the image data of a preset part of the preset area based on the first image data, and then determine the first reference plane of the preset area based on the image data of the preset part.

[0113] Specifically, the preset location within the preset region can be the outer wall of the preset region, bones within the preset region, or organs within the preset region that satisfy a preset shape. The outer wall of the preset region refers to its peripheral area. For example, the preset region could be the head, chest, or abdomen of the human body, with the corresponding outer walls being the outer walls of the head, chest, and abdomen, respectively. Organs satisfying the preset shape can be organs with approximately symmetrical structures; for example, organs without disease are approximately symmetrical. The electronic device can determine a first reference plane for the preset location within the preset region and use this first reference plane as the first reference plane for the preset region.

[0114] For example, such as Figure 4 As shown, the outer wall of the abdomen (i.e., the abdominal wall) 41 is the peripheral region of the abdomen. The electronic device determines candidate planes of symmetry based on the length or shape of the abdominal wall, then determines the similarity between the image of the abdominal wall rotated around the candidate planes of symmetry and the abdominal wall itself, and finally determines the first reference plane from the candidate planes of symmetry. Alternatively, the electronic device determines candidate planes of symmetry based on the length or shape of the chest wall, then determines the similarity between the image of the chest wall rotated around the candidate planes of symmetry and the chest wall itself, and finally determines the first reference plane from the candidate planes of symmetry. When organs within the human body become diseased, the overall shape of the human body region changes. Determining the first plane of symmetry by using the outer wall of the human body region, the bones within the human body region, and the disease-free organs within the human body region can avoid interference from images inside or outside the human body region, improving the accuracy of the calculation results.

[0115] In one embodiment, the electronic device rotates a preset area, and stops rotating when it determines that the first reference object of the preset area is parallel, coincident, or nearly coincident with the second reference object of the support surface, and determines rotation data based on the rotation angle of the preset area.

[0116] Specifically, when the first reference object and the second reference object are parallel, coincident, or nearly coincident, the rotation angle of the preset region is the angle between the first and second reference objects. The rotation angle can be determined based on the positions of the first and second reference objects. Taking a human body region as an example, and the image of the preset region as a 3D image. Figure 5As shown, the supporting surface is the bed board of the second imaging device. The second reference object 52 of the bed board 51 is a plane perpendicular to the bed board, i.e., the second reference plane. The first reference object is the first reference plane. A coordinate system is established with the center of the preset area as the origin, the left-right direction of the human body as the x-axis, and the front-back direction of the human body as the y-axis. The projection of the first reference plane on the xoy plane can be determined based on the position of the first reference plane. The projection of the second reference plane on the xoy plane can be determined based on the position of the second reference plane. The angle between the projection of the first reference plane and the projection of the second reference plane is the angle between the first reference plane and the second reference plane, i.e., the rotation angle α.

[0117] like Figure 6 As shown, the human body region is rotated by α around the head-to-toe direction. If the first reference plane deflects to the left relative to the second reference plane, the human body is rotated counterclockwise; if the first reference plane deflects to the right relative to the second reference plane, the human body is rotated clockwise, thus aligning the first and second reference planes. At this point, the human body region is in a straight position on the bed. The electronic device can obtain the rotation data of the human body region when rotated by α around the head-to-toe direction according to the Rodrigues rotation formula. The Rodrigues rotation formula is used to calculate the new vector obtained by rotating a vector in three-dimensional space by a specified angle along the rotation axis. For example, the rotation data can be represented by a matrix, namely the rotation matrix R, which is calculated as R = I + (sinα)K + (1 - cosα)K. 2 K represents the rotation vector of the first plane of symmetry, and I represents the identity matrix.

[0118] In one embodiment, the method for determining the offset data is as follows: after rotating the preset area according to the rotation data, the preset area is moved. When the distance between the first preset position and the second preset position is less than the first preset distance, the moving distance of the preset area is taken as the first offset. The preset area is moved on the second reference object. When the closest distance between the preset area and the support surface is less than the second preset distance, the second offset of the preset area is determined. The offset data is determined according to the first offset and the second offset.

[0119] In this process, after rotating the preset area according to the rotation data, the target object is positioned upright on the support surface. Once the target object is upright on the support surface, further offsetting of the preset area allows the target object to be moved to a specified position on the support surface.

[0120] In one embodiment, the electronic device moves the preset area based on the positional relationship between the point cloud data of the preset area and the point cloud data of the supporting surface.

[0121] Specifically, after rotating the preset area according to the rotation data, the electronic device determines the first projection data of the preset area on the preset plane based on the point cloud data of the preset area, and determines the second projection data of the support surface on the preset plane based on the point cloud data of the support surface. Then, the electronic device calculates the center point of the first projection data and uses it as the first preset position; it then calculates the center point of the second projection data and uses it as the second preset position. The preset plane is perpendicular to the plane containing the support surface. For example, if the target object is a human body and the support surface is a bed board, the preset plane is perpendicular to the plane containing the human body area. It can be the xoy plane of a preset coordinate system, where the x-axis represents the left-right direction of the human body, the y-axis represents the front-back direction of the human body, and the z-axis represents the head-to-toe direction of the human body.

[0122] like Figure 7 As shown, after determining the first preset position and the second preset position, a preset area is moved within a preset plane. When the distance between the first preset position and the second preset position is less than the first preset distance, the electronic device uses the movement distance of the preset area in the coordinate system as the first offset. Specifically, when the distance between the first preset position and the second preset position is less than the first preset distance, the first preset position and the second preset position nearly coincide. If the image of the preset area is a three-dimensional image, the first offset is the offset of the point cloud data of the preset area in the xoy plane, that is, the first offset includes at least one of the offset of the point cloud data of the preset area in the x-direction and the offset in the y-direction. If the image of the preset area is a two-dimensional image, the first offset is the offset of the point cloud data of the preset area in the x-direction.

[0123] Next, the preset area is moved in the vertical direction (i.e., the y-direction) of the support surface. When the electronic device determines that the closest distance between the preset area and the support surface is less than the second preset distance, it stops moving. At this time, the center position of the preset area is aligned with the center position of the support surface, and the preset area is separated from the support surface by a certain distance. The moving distance of the preset area is taken as the second offset. The first offset and the second offset are the offset data, which can be represented by a matrix.

[0124] In one embodiment, when the first preset position coincides with the second preset position, the human body area moves in the vertical direction of the support surface according to a preset step size, for example, the preset step size can be 1 millimeter. Figure 8As shown, when the closest distance between the preset region and the support surface is less than the second preset distance, the moving distance of the preset region is taken as the second offset. The closest distance between the preset region and the support surface can be the distance between the two closest points in the point cloud data of the preset region and the point cloud data of the support surface. When the distance between the two closest points is greater than or equal to the preset step length and less than 2 times the preset step length, the closest distance between the preset region and the support surface is less than the second preset distance, and at this time, the preset region is located at the preset position of the support surface.

[0125] As shown in the embodiment, the human body region is rotated according to the rotation data, and then the human body region is moved according to the first offset and the second offset. Figure 9 As shown, the human body region is located in the center region of the bed board, and the human body and the bed board are just separated.

[0126] In an embodiment, the medical image data generation method provided by the embodiment of the present application is applied to a medical system. As shown in the embodiment, Figure 10 The medical system includes an electronic device 100 for executing the medical image data generation method, a path planning device 200, and a robot 300. The electronic device 100 is configured to adopt the medical image data generation method, obtain second image data from the first image data, and send the second image data to the path planning device 200. The path planning device 200 plans a path for the robot 300 to perform surgery according to the region to be operated. Then, the electronic device 100 can obtain the planned surgical path from the path planning device 200, and perform 3D space modeling according to the second image data, the point cloud data of the bed board, and the position of the external obstacle. The electronic device 100 determines whether the planned surgical path is feasible according to the robot model and the environment model. If the surgical path is determined to be feasible, the electronic device 100 instructs the robot 300 to perform surgery according to the planned surgical path.

[0127] It should be understood that the size of the serial number of each step in the above embodiment does not mean the order of execution. The execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0128] According to the image data generation method described in the above embodiment, Figure 10 The structure block diagram of the medical image data generation device provided by the embodiment of the present application is shown. For ease of illustration, only the parts related to the embodiment of the present application are shown.

[0129] As shown in the embodiment, Figure 11 The medical image data generation device includes:

[0130] The acquisition module 111 is configured to acquire first image data, which is obtained from the image data of a target object collected by a first image device.

[0131] The symmetry surface determination module 112 is configured to determine a first reference object of a preset region of the target object according to the first image data.

[0132] The rotation data determination module 113 is configured to determine rotation data of the preset region according to a positional relationship between the first reference object and a second reference object of a second image device, the second image device being an image device matched with the interventional robot, and the second reference object being a symmetry surface or a symmetry axis of a support surface of the second image device.

[0133] The offset data determination module 114 is configured to determine offset data according to a distance between a first preset position of the preset region and a second preset position of the support surface.

[0134] The conversion module 115 is configured to determine second image data of the target object under the second image device according to the first image data, the rotation data and the offset data.

[0135] In an embodiment, the symmetry surface determination module 112 is specifically configured to:

[0136] determine an image of the preset region according to the first image data;

[0137] determine a similarity between an image of the preset region after being rotated around each candidate object and the image of the preset region, the candidate object being obtained according to a preset algorithm;

[0138] take the candidate object corresponding to the maximum similarity as the first reference object.

[0139] In an embodiment, the symmetry surface determination module 112 is specifically configured to:

[0140] determine image data of a preset part of the preset region according to the first image data, the preset part including any one or more of an outer wall of the preset region, a bone in the preset region, and an organ in the preset region satisfying a preset shape;

[0141] determine the first reference object of the preset region according to the image data of the preset part.

[0142] In an embodiment, the offset data determination module 114 is specifically configured to:

[0143] after rotating the preset region according to the rotation data, move the preset region, and when a distance between the first preset position and the second preset position is less than a first preset distance, take a moving distance of the preset region as a first offset amount.

[0144] moving the preset region on the second reference object, determining a second offset of the preset region when a nearest distance between the preset region and the support surface is less than a second preset distance;

[0145] determining the offset data according to the first offset and the second offset.

[0146] In an embodiment, the offset data determining module 114 is specifically configured to:

[0147] moving the preset region according to a positional relationship between point cloud data of the preset region and point cloud data of the support surface.

[0148] In an embodiment, the obtaining module 111 is specifically configured to:

[0149] obtaining original image data obtained by the first image device scanning the target object;

[0150] determining body position conversion data according to a first body position when the first image device scans the target object and a second body position corresponding to the second image device;

[0151] determining the first image data according to the original image data and the body position conversion data.

[0152] In an embodiment, the obtaining module 111 is specifically configured to:

[0153] scaling an image corresponding to the original image data according to a device parameter when the first image device scans the target object and a device parameter of the second image device, to obtain scaled image data;

[0154] determining the first image data according to the scaled image data and the body position conversion data.

[0155] It should be noted that the information interaction, execution process and the like between the above apparatuses / units are based on the same concept as the method embodiments of the present application, and the specific functions and technical effects brought by the same can be referred to the method embodiments part, and will not be repeated here.

[0156] Figure 12 is a structural schematic diagram of an electronic device provided by the present embodiment, and the electronic device can be a desktop computer, a notebook computer, a palm computer or the like.

[0157] As shown in FIG. 1, the electronic device 100 includes a processor 110, a memory 120 and a communication interface 130. Figure 12As shown, the electronic device of the embodiment includes a processor 121, a memory 122, and a computer program 123 stored in the memory 122 and executable on the processor 121. The processor 121 implements the steps in the above-mentioned embodiment of the method for generating image data when executing the computer program 123, for example Figure 1 As shown, the steps S101 to S105. Alternatively, the processor 121 implements the functions of each module / unit in the above-mentioned embodiments of the apparatus when executing the computer program 123, for example Figure 11 As shown, the functions of the obtaining module 111 to the conversion module 115.

[0158] Illustratively, the computer program 123 can be segmented into one or more modules / units, which are stored in the memory 122 and executed by the processor 121 to complete the present application. The one or more modules / units can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program 123 in the electronic device.

[0159] Those skilled in the art can understand that Figure 12 The electronic device is only an example and does not constitute a limitation on the electronic device, which can include more or fewer components than shown, or combine certain components, or different components, for example, the electronic device can also include an input / output device, a network access device, a bus, etc.

[0160] The processor 121 can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0161] The memory 122 can be an internal storage unit of the electronic device, such as a hard disk or a memory of the electronic device. The memory 122 can also be an external storage device of the electronic device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, or the like equipped on the electronic device. Further, the memory 122 can include both the internal storage unit and the external storage device of the electronic device. The memory 122 is used to store the computer program and other programs and data required by the electronic device. The memory 122 can also be used to temporarily store data that has been output or will be output.

[0162] It should be clearly understood by those skilled in the art that, for the convenience and brevity of description, only the above-mentioned division of each functional unit and module is exemplified, and in actual application, the above-mentioned functions can be completed by different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction, and do not limit the protection scope of the present application. The specific working process of the unit and module in the above system can refer to the corresponding process in the foregoing method embodiment, which will not be repeated here.

[0163] In the above embodiments, the description of each embodiment has its own emphasis, and the parts not described or recorded in detail in a certain embodiment can be referred to the related description of other embodiments.

[0164] In the embodiments provided in the present application, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are only schematic, and the division of the modules or units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed mutual units can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0165] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, i.e. may be located in one place, or may be distributed on multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0166] The integrated modules / units, if implemented in the form of software functional units and sold or used as independent products, can be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. When the processor executes the computer program, the steps of the above-mentioned various method embodiments can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable file or some intermediate form. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0167] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0168] The above-described embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A method of generating medical image data, characterized by, The method comprises the following steps: acquiring first image data, which is image data of a target object collected by a first image device; determining a first reference object of a preset region of the target object according to the first image data; determining rotation data of the preset region according to a positional relationship between the first reference object and a second reference object of a second image device, the second image device being an image device matched with an interventional robot, and the second reference object being a symmetrical surface or a symmetrical axis of a support surface of the second image device; determining offset data according to a distance between a first preset position of the preset region and a second preset position of the support surface; determining second image data of the target object under the second image device according to the first image data, the rotation data and the offset data.

2. The method of claim 1, wherein, The method comprises the following steps: determining an image of the preset region according to the first image data; determining a similarity between an image of the preset region after rotation around each candidate object and the image of the preset region, the candidate object being obtained according to a preset algorithm; taking the candidate object corresponding to the maximum similarity as the first reference object.

3. The method of claim 1, wherein, The method comprises the following steps: determining image data of a preset part of the preset region according to the first image data, the preset part including any one or more of an outer wall of the preset region, a bone in the preset region and an organ in the preset region satisfying a preset shape; determining the first reference object of the preset region according to the image data of the preset part.

4. The method of claim 1, wherein, The method comprises the following steps: rotating the preset region according to the rotation data, and moving the preset region, when a distance between the first preset position and the second preset position is less than a first preset distance, taking a moving distance of the preset region as a first offset; moving the preset region on the second reference object, and determining a second offset of the preset region when a closest distance between the preset region and the support surface is less than a second preset distance; determining the offset data according to the first offset and the second offset.

5. The method of claim 4, wherein, The method comprises the following steps: moving the preset region according to a positional relationship between point cloud data of the preset region and point cloud data of the support surface.

6. The method according to any one of claims 1 to 5, characterized in that, The method comprises the following steps: acquiring original image data of the target object scanned by the first image device; determining body position conversion data according to a first body position when the first image device scans the target object and a second body position corresponding to the second image device; determining the first image data according to the original image data and the body position conversion data.

7. The method of claim 6, wherein, The method comprises the following steps: According to the device parameter when the first imaging device scans the target object and the device parameter of the second imaging device, the image corresponding to the original image data is scaled to obtain scaled image data; According to the scaled image data and the body position conversion data, the first image data is determined.

8. An apparatus for generating medical image data, characterized by Comprise: The acquisition module is used for acquiring first image data, and the first image data is obtained from image data of a target object collected by a first imaging device; The symmetry surface determination module is used for determining a first reference object of a preset region of the target object according to the first image data; The rotation data determination module is used for determining rotation data of the preset region according to a position relationship between the first reference object and a second reference object of a second imaging device, the second imaging device being an imaging device matched with an interventional robot, and the second reference object being a symmetry surface or a symmetry axis of a support surface of the second imaging device; The offset data determination module is used for determining offset data according to a distance between a first preset position of the preset region and a second preset position of the support surface; The conversion module is used for determining second image data of the target object under the second imaging device according to the first image data, the rotation data and the offset data.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to realize the method in any one of claims 1-7.

10. A medical system, characterized by The electronic device comprises a robot, a path planning device and the electronic device in claim 9, and the path planning device is used for planning a path of the robot according to the second image data. 11.A computer readable storage medium, storing a computer program, characterized in that, The computer program is executed by the processor to realize the method in any one of claims 1-7.

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