Collision detection method and device, storage medium and electronic equipment

Abstract

The invention discloses a collision detection method and device, a storage medium and electronic equipment, and the method comprises the steps: collecting image data of a C-shaped arm image device, an operating bed and a space region where a patient is located from different angles through image collection devices disposed on the inner surface of a C-shaped arm influence device; according to the technical scheme, the three-dimensional environment model including the C-shaped arm image equipment, the operating bed and the patient is constructed according to the collected image data, so that virtual anti-collision detection can be performed based on the constructed three-dimensional environment model, the collision detection result is given, and the collision detection efficiency can be improved.

Description

Technical Field

[0001] This specification relates to the field of computer vision technology, and in particular to a collision detection method, apparatus, storage medium, and electronic device. Background Technology

[0002] Currently, when acquiring images using X-ray imaging equipment (such as C-arm imaging equipment), the X-ray imaging equipment can be controlled to move freely around the patient and release X-rays to image from multiple angles. This allows doctors to observe the lesion from the best perspective, accurately locate the lesion tissue, fracture site, or implant position, thereby ensuring the accuracy and safety of the surgical procedure.

[0003] Typically, before 3D image acquisition using X-ray imaging equipment, collision detection of the equipment hardware is required. This involves the doctor manually controlling the X-ray imaging equipment to "simulate" its movement along a predetermined path (with the X-ray source off) to check for obstacles around the patient and operating table, and to confirm whether collisions will occur within the range of motion of the robotic arm. However, during the collision detection process, if a potential collision is detected, or if a collision occurs due to the doctor's inability to detect an obstacle in time due to viewing angle limitations, the collision detection process is stopped. In this case, the equipment needs to be reset to its initial position and the collision detection repeated, resulting in low efficiency.

[0004] Therefore, how to improve the efficiency of collision detection in X-ray imaging equipment is an urgent problem to be solved. Summary of the Invention

[0005] This specification provides a collision detection method, apparatus, storage medium, and electronic device to partially solve the aforementioned problems existing in the prior art.

[0006] The following technical solution is adopted in this specification:

[0007] This specification provides a collision detection method applied to a C-arm imaging device. Image acquisition devices are disposed at first and second designated positions on the inner surface of the C-arm imaging device, the first and second designated positions being located on either side of the midpoint of the arc length of the inner surface of the C-arm imaging device. The method includes:

[0008] Get a collision detection request;

[0009] Based on the collision detection request, the initial detection angle and the termination detection angle of the C-arm imaging device are determined, and image data of a specified spatial area are acquired by each image acquisition device as reference image data. The specified spatial area contains at least one target object.

[0010] Based on the reference image data, a target three-dimensional environment model is constructed, which includes a three-dimensional representation of the C-arm imaging device and the target object.

[0011] Based on the target 3D environment model, the collision detection results of the C-arm imaging device during its operation from the initial detection angle to the final detection angle are determined, and the collision detection results are displayed to the user. The collision detection results are used to reflect whether the C-arm imaging device will collide during operation.

[0012] Optionally, based on the reference image data, a target 3D environment model is constructed, specifically including:

[0013] Each reference image data is detected to determine each feature point contained in each reference image data;

[0014] For each feature point, the disparity map corresponding to each reference image data is determined based on the displacement of the feature point between its positions in different reference image data.

[0015] Based on the positional relationship between the image acquisition devices and the disparity map, a target 3D environment model is constructed.

[0016] Optionally, the inner surface of the C-arm imaging device is further provided with at least one other image acquisition device;

[0017] Image data of a specified spatial region is acquired through various image acquisition devices and used as reference image data, specifically including:

[0018] Image data of a specified spatial region is acquired using the image acquisition device and other image acquisition devices, and used as reference image data.

[0019] Based on the reference image data, a target 3D environment model is constructed, specifically including:

[0020] Each reference image data is detected to determine each feature point contained in each reference image data;

[0021] For every two reference image data in each of the aforementioned reference image data, based on each feature point in

[0022] The displacement between the positions in every two reference image data points is used to determine the disparity map corresponding to each pair of reference image data points, which serves as the reference disparity map.

[0023] The disparity maps of each reference image are fused to obtain the disparity map corresponding to each reference image data. Based on the positional relationship between each image acquisition device and the disparity map, a target three-dimensional environment model is constructed.

[0024] Optionally, based on the positional relationship between the image acquisition devices and the disparity map, a target 3D environment model is constructed, specifically including:

[0025] Based on the positional relationship between the image acquisition devices and the disparity map, the distance between each feature point in the reference image data and the C-arm imaging device is determined.

[0026] Based on the distance, a depth map of the specified spatial region is determined, and a target three-dimensional environment model is constructed based on the depth map and the positional relationship between the image acquisition devices.

[0027] Optionally, the collision detection results are displayed to the user, specifically including:

[0028] If, based on the collision detection results, it is determined that the C-arm imaging device will collide with a target object contained within the specified spatial area during operation, then the target object that collides with the C-arm imaging device is identified as the target object to be marked.

[0029] In the target 3D environment model, the target object to be marked is marked to obtain the marked target 3D environment model, and the marked target 3D environment model is displayed to the user.

[0030] Optionally, the C-arm imaging device has grooves at both the first designated position and the second designated position, and the image acquisition device is disposed in the grooves. The opening of the grooves is sealed by a transparent material.

[0031] This specification also provides a collision detection device for operating a collision detection method applied to a C-arm imaging device. Image acquisition devices are disposed at a first designated position and a second designated position on the inner surface of the C-arm imaging device. The first designated position and the second designated position are respectively located on both sides of the midpoint of the arc length of the inner surface of the C-arm imaging device. The device includes:

[0032] The receiving module is used to acquire collision detection requests;

[0033] The determination module is used to determine the initial detection angle and the termination detection angle of the C-arm imaging device according to the collision detection request, and to collect image data of a specified spatial area through each image acquisition device as reference image data, wherein the specified spatial area contains at least one target object;

[0034] The construction module is used to construct a target three-dimensional environment model based on the reference image data, wherein the target three-dimensional environment model includes a three-dimensional representation of the C-arm imaging device and the target object;

[0035] The detection module is used to determine the collision detection results of the C-arm imaging device during its operation from the initial detection angle to the final detection angle based on the target three-dimensional environment model, and to display the collision detection results to the user. The collision detection results are used to reflect whether the C-arm imaging device will collide during operation.

[0036] Optionally, the construction module is specifically used to: detect each reference image data to determine each feature point contained in each reference image data; for each feature point, determine the disparity map corresponding to each reference image data based on the displacement between the positions of the feature point in different reference image data; and construct a target three-dimensional environment model based on the positional relationship between each image acquisition device and the disparity map.

[0037] This specification provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described collision detection method.

[0038] This specification provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described collision detection method.

[0039] The above-mentioned technical solutions adopted in this specification can achieve the following beneficial effects:

[0040] In this specification, the server can receive collision detection requests, determine the initial and final detection angles of the C-arm imaging device based on the received collision detection requests, and collect image data of a specified spatial area through various image acquisition devices as reference image data. The specified spatial area contains at least one target object. Then, based on the reference image data, a target 3D environment model is constructed, and the constructed target 3D environment model includes 3D representations of the C-arm imaging device and the target object. Based on the target 3D environment model, the collision detection results of the C-arm imaging device during its operation from the initial detection angle to the final detection angle are determined, and the collision detection results are displayed to the user. The collision detection results here are used to reflect whether a collision will occur during the operation of the C-arm imaging device.

[0041] As can be seen from the above, by setting up various image acquisition devices on the inner surface of the C-arm imaging device, image data of the C-arm imaging device, the operating table, and the spatial area where the patient is located are collected from different angles. Based on the collected image data, a three-dimensional environment model containing the C-arm imaging device, the operating table, and the patient is constructed. Virtual collision avoidance detection can then be performed based on the constructed three-dimensional environment model, and collision detection results can be provided, thereby improving the efficiency of collision detection. Attached Figure Description

[0042] The accompanying drawings, which are included to provide a further understanding of this specification and form part of this specification, illustrate exemplary embodiments and are used to explain this specification, but do not constitute an undue limitation thereof. In the drawings:

[0043] Figure 1 This is a schematic diagram of the C-arm imaging device provided in this manual.

[0044] Figure 2 This is a flowchart illustrating a collision detection method provided in this specification;

[0045] Figure 3 This is a schematic diagram of the first and second designated locations provided in this specification;

[0046] Figure 4 This is a schematic diagram showing the location of other image acquisition devices provided in this manual;

[0047] Figure 5 This is a schematic diagram of the collision detection device provided in this specification;

[0048] Figure 6 The corresponding to the information provided in this specification Figure 1 A schematic diagram of the structure of an electronic device. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this specification clearer, the technical solutions of this specification will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of them. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this specification.

[0050] In the medical field, C-arm imaging equipment is a commonly used medical device, mainly composed of a workstation, a C-arm, a flat panel detector, and an X-ray tube, as detailed below. Figure 1 As shown.

[0051] Figure 1 This is a schematic diagram of the C-arm imaging device provided in this manual.

[0052] Combination Figure 1 As can be seen, when doctors acquire patient image information using C-arm imaging equipment, they can control the C-arm to rotate around the patient and the operating table by performing touch operations on the monitor included in the workstation. During the rotation of the C-arm, the X-ray tube emits X-rays, and the flat panel detector receives the X-rays passing through the patient's affected area to acquire images of the affected area. These images can then be displayed on the monitor to the doctor in front of the workstation.

[0053] Before this, the doctor needs to manually control the C-arm to rotate along the path required to acquire the patient's image information while the X-ray tube is closed. The doctor must observe the patient and the area around the operating table for any obstacles. If a collision is detected within the range of motion of the C-arm, the collision detection is stopped and the C-arm imaging device is reset to its initial position. The collision detection process can then be repeated after the obstacle causing the collision is removed.

[0054] As can be seen from the above, collision detection using C-arm imaging equipment relies entirely on the doctor's observation. However, in clinical practice, the observation angle may prevent the doctor from observing potential collisions in a timely manner. Furthermore, after a collision occurs, the collision detection process needs to be restarted after the obstacle is removed. Consequently, the collision detection efficiency of C-arm imaging equipment is low, and the safety of collision detection is poor.

[0055] The technical solutions provided in the various embodiments of this specification are described in detail below with reference to the accompanying drawings.

[0056] This specification provides a collision detection method, such as Figure 2As shown.

[0057] Figure 2 This is a flowchart illustrating a collision detection method provided in this specification, including the following steps:

[0058] S201: Get collision detection request.

[0059] In this specification, the C-arm imaging device can determine the control commands input by the user based on the touch operation performed by the user on the monitor in the workstation, and can obtain collision detection requests based on the received control commands. Then, based on the obtained collision detection requests, it controls the image acquisition device deployed on the C-arm imaging device to acquire image data of a specified spatial area during the operation of the C-arm imaging device, and determines the collision detection results based on the acquired image data, and displays the collision detection results to the user through the monitor.

[0060] The C-arm imaging device described above can have at least two image acquisition devices installed on its inner surface. When two image acquisition devices are installed on the inner surface of the C-arm, these two devices can be respectively positioned at a first designated position and a second designated position on the inner surface of the C-arm. The first and second designated positions can be located on either side of the midpoint of the arc length on the inner surface of the C-arm. The midpoint of the arc length, as mentioned above, refers to the point that divides the arc of the inner surface of the C-arm into three equal-length arc segments. For ease of understanding, the first and second designated positions on the C-arm imaging device will be described in detail below, as follows: Figure 3 As shown.

[0061] Figure 3 This is a schematic diagram of the first and second designated positions provided in this specification.

[0062] Combination Figure 3 It can be seen that the first and second designated positions mentioned above can be located at the third point on the inner surface of the C-arm. Here, the third point refers to the two points used to divide the arc of the inner surface of the C-arm into three arcs of equal length.

[0063] It should be noted that by placing the image acquisition device on the inner surface of the C-arm, the influence of external environmental factors can be effectively reduced. For example, the impact of changes in light on the quality of image data acquired by the image acquisition device, the impact of dust on the quality of image data acquired by the image acquisition device, the impact of moisture on the quality of image data acquired by the image acquisition device, etc., can also prevent the C-arm from coming into contact with other equipment or personnel during the operation, thereby avoiding damage to the image acquisition device.

[0064] In addition, the first and second designated positions mentioned above can also be located at both ends of the C-arm of the C-arm imaging device, that is, the outside of the X-ray tube and the outside of the flat panel detector. In this case, the first and second designated positions of the C-arm imaging device can also be provided with grooves, so that the image acquisition device can be placed in the groove of the first and second designated positions. The opening of the groove at the first designated position and the opening of the groove at the second designated position are both sealed with transparent material.

[0065] The aforementioned transparent materials can refer to materials that allow visible light to pass through almost unimpeded, such as glass, transparent plastics, and transparent ceramics.

[0066] In this specification, the execution subject for implementing the collision detection method can refer to a designated device such as a server used to remotely control the C-arm imaging equipment, or it can refer to a terminal device such as a desktop computer or laptop computer set up in the C-arm imaging equipment workstation. For ease of description, the collision detection method provided in this specification will be described below using the terminal device as the execution subject as an example.

[0067] S202: Based on the collision detection request, determine the initial detection angle and the termination detection angle of the C-arm imaging device, and collect image data of a specified spatial area through each image acquisition device as reference image data. The specified spatial area contains at least one target object.

[0068] In this specification, after receiving a collision detection request, the terminal device can determine the initial angle of rotation of the C-arm imaging device during the subsequent acquisition of patient image information, as the initial detection angle, and determine the termination angle of rotation of the C-arm imaging device during the subsequent acquisition of patient image information, as the termination detection angle.

[0069] Furthermore, for each image acquisition device installed on the C-arm imaging equipment, the terminal device can acquire image data of a specified spatial area through the image acquisition device as reference image data.

[0070] Since different image acquisition devices are set in different locations, the different reference image data acquired are image data of a specified spatial area from different perspectives.

[0071] In practical applications, to improve the accuracy of collision detection for C-arm imaging devices, the inner surface of the C-arm of the aforementioned C-arm imaging device can also be equipped with at least one other image acquisition device, specifically as follows: Figure 4 As shown.

[0072] Figure 4This is a schematic diagram showing the location of other image acquisition devices provided in this manual.

[0073] Combination Figure 4 It can be seen that other image acquisition devices can also be installed at the midpoint of the inner surface curve of the C-arm of the aforementioned C-arm imaging device, the upper vertex of the inner surface curve of the C-arm, the lower vertex of the inner surface curve of the C-arm, and the two endpoints of the inner surface curve of the C-arm. Figure 3 In the diagram, the area marked by the dashed box is the specified spatial region.

[0074] Furthermore, the terminal device can acquire image data of a specified spatial area using an image acquisition device located at a first designated position on the inner surface of the C-arm, an image acquisition device located at a second designated position on the inner surface of the C-arm, and the other image acquisition devices mentioned above, as reference image data.

[0075] It should be noted that the designated space area mentioned above contains at least one target object, which may be an obstacle such as a patient, the patient's operating table, other surgical equipment, or other personnel.

[0076] S203: Based on the reference image data, construct a target three-dimensional environment model, wherein the target three-dimensional environment model includes a three-dimensional representation of the C-arm imaging device and the target object.

[0077] Furthermore, after acquiring each reference image data, the terminal device can detect each reference image data to determine each feature point contained in each reference image data. Then, for each feature point, based on the displacement between the positions of the feature point in different reference image data, the disparity map corresponding to each reference image data can be determined. Based on the positional relationship between each image acquisition device and the disparity map corresponding to each reference image data, a target three-dimensional environment model can be constructed.

[0078] In the above content, the feature points contained in each reference image data can be set according to actual needs, such as: the pixels that make up the outline of the target object, the corner points of the target object, etc.

[0079] In the above content, each element in the disparity map is used to represent the displacement of each feature point between its positions in different reference image data.

[0080] In the above content, the method by which the terminal device determines the displacement between the positions of the feature point in different reference image data can be as follows: select an image region of a specified size with the feature point as the center point from the reference image data acquired by the image acquisition device located at the first specified position, as the target image block, and identify the image block with the highest similarity to the target image block from the reference image data acquired by the image acquisition device located at the first specified position, as the reference image block. Then, the horizontal displacement between the target image block and the reference image block can be determined as the displacement between the positions of the feature point in different reference image data.

[0081] In practical applications, the number of reference image data can be greater than three. When the number of reference image data is greater than three, the terminal device can detect each reference image data to determine the feature points contained in each reference image data. Then, for each pair of reference image data, based on the displacement between the positions of each feature point in each pair of reference image data, the disparity map corresponding to each pair of reference image data can be determined as a reference disparity map. The reference disparity maps can then be fused to obtain the disparity map corresponding to each reference image data. Based on the positional relationship between each image acquisition device and the disparity map corresponding to each reference image data, a target 3D environment model can be constructed.

[0082] Specifically, the terminal device can determine the distance between each feature point in each reference image data and the C-arm imaging device based on the positional relationship between each image acquisition device and the disparity map. Then, based on the distance between each feature point in each reference image data and the C-arm imaging device, it can determine the depth map of the specified spatial area and construct the target three-dimensional environment model based on the depth map of the specified spatial area and the positional relationship between each image acquisition device.

[0083] The depth map mentioned above can be a two-dimensional array, and each element in the depth map can be used to characterize the distance between each feature point contained in each reference image data and the C-arm imaging device.

[0084] S204: Based on the target 3D environment model, determine the collision detection results of the C-arm imaging device during its operation from the initial detection angle to the final detection angle, and display the collision detection results to the user. The collision detection results are used to reflect whether the C-arm imaging device will collide during operation.

[0085] In this specification, after the terminal device constructs the target three-dimensional environment model corresponding to the specified spatial area, it can determine the collision detection results of the C-arm imaging device during the process of running from the initial detection angle to the final detection angle based on the target three-dimensional environment model, and display the collision detection results to the user.

[0086] The collision detection results mentioned above are used to reflect whether the C-arm imaging equipment will collide during operation.

[0087] Specifically, the terminal device can determine, based on the collision detection results, when a collision occurs between the C-arm imaging device and a target object within a specified spatial area during operation, and identify the target object that collides with the C-arm imaging device as the target object to be marked. Then, the target object to be marked can be marked in the target 3D environment model to obtain the marked target 3D environment model, and the marked target 3D environment model can be displayed to the user.

[0088] The marking process described above can be used to highlight the target object to be marked, or it can be used to render the target object with a specified color.

[0089] As can be seen from the above, the terminal device can acquire image data of the C-arm imaging device, the operating table, and the patient's spatial area from different angles through various image acquisition devices set on the inner surface of the C-arm imaging device. Based on the acquired image data, a three-dimensional environment model containing the C-arm imaging device, the operating table, and the patient can be constructed. Virtual collision avoidance detection can then be performed based on the constructed three-dimensional environment model, and collision detection results can be provided, thereby improving the efficiency of collision detection.

[0090] The above describes one or more methods for implementing collision detection in this specification. Based on the same approach, this specification also provides corresponding collision detection devices, such as... Figure 5 As shown.

[0091] Figure 5 A schematic diagram of the collision detection device provided in this specification includes:

[0092] Receiver module 501 is used to acquire collision detection requests;

[0093] The determining module 502 is used to determine the initial detection angle and the final detection angle of the C-arm imaging device according to the collision detection request, and to collect image data of a specified spatial area through each image acquisition device as reference image data, wherein the specified spatial area contains at least one target object;

[0094] Construction module 503 is used to construct a target three-dimensional environment model based on the reference image data, wherein the target three-dimensional environment model includes a three-dimensional representation of the C-arm imaging device and the target object;

[0095] The detection module 504 is used to determine the collision detection results of the C-arm imaging device during its operation from the initial detection angle to the final detection angle based on the target three-dimensional environment model, and to display the collision detection results to the user. The collision detection results are used to reflect whether the C-arm imaging device will collide during operation.

[0096] Optionally, the construction module 503 is specifically used to: detect each reference image data to determine each feature point contained in each reference image data; for each feature point, determine the disparity map corresponding to each reference image data based on the displacement between the positions of the feature point in different reference image data; and construct a target three-dimensional environment model based on the positional relationship between each image acquisition device and the disparity map.

[0097] Optionally, the inner surface of the C-arm imaging device is further provided with at least one other image acquisition device;

[0098] The determining module 502 is specifically used to acquire image data of a specified spatial region through the image acquisition device and the other image acquisition devices, and use it as reference image data.

[0099] The construction module 503 is specifically used to: detect each reference image data to determine each feature point contained in each reference image data; for each pair of reference image data, determine the disparity map corresponding to each pair of reference image data based on the displacement between the positions of each feature point in each pair of reference image data, and use it as a reference disparity map; fuse the reference disparity maps to obtain the disparity map corresponding to each reference image data, and construct a target three-dimensional environment model based on the positional relationship between each image acquisition device and the disparity map.

[0100] Optionally, the construction module 503 is specifically used to: determine the distance between each feature point contained in each reference image data and the C-arm imaging device based on the positional relationship between the image acquisition devices and the disparity map; determine the depth map of the specified spatial region based on the distance; and construct a target three-dimensional environment model based on the depth map and the positional relationship between the image acquisition devices.

[0101] Optionally, the detection module 504 is specifically used to: if, based on the collision detection result, it is determined that the C-arm imaging device will collide with a target object contained in the specified spatial area during operation, then determine the target object that collides with the C-arm imaging device as a target object to be marked; mark the target object to be marked in the target 3D environment model to obtain a marked target 3D environment model, and display the marked target 3D environment model to the user.

[0102] Optionally, the C-arm imaging device has grooves at both the first designated position and the second designated position, and the image acquisition device is disposed in the grooves. The opening of the grooves is sealed by a transparent material.

[0103] This specification also provides a computer-readable storage medium storing a computer program that can be used to execute the above-described... Figure 1 A collision detection method is provided.

[0104] This instruction manual also provides Figure 6 One of the corresponding Figure 1 A schematic diagram of the structure of an electronic device. (e.g.) Figure 6 At the hardware level, the electronic device includes a processor, internal bus, network interface, memory, and non-volatile memory, and may also include other hardware required for the business operations. The processor reads the corresponding computer program from the non-volatile memory into memory and then runs it to achieve the above-mentioned functions. Figure 1 The collision detection method described above. Of course, in addition to software implementation, this specification does not exclude other implementation methods, such as logic devices or a combination of hardware and software, etc. That is to say, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0105] Improvements in a technology can be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many improvements to the methodology can now be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that an improvement in methodology cannot be implemented using hardware physical modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program and "integrate" a digital system onto a PLD themselves, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog are the most commonly used. Those skilled in the art should understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0106] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0107] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0108] For ease of description, the above devices are described in terms of function, divided into various units. Of course, in implementing this specification, the functions of each unit can be implemented in one or more software and / or hardware components.

[0109] Those skilled in the art will understand that embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this specification may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0110] This specification is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this specification. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0111] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0112] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0113] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0114] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0115] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0116] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0117] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this specification may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0118] This specification can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This specification can also be practiced in distributed computing environments, where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0119] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0120] The above description is merely an embodiment of this specification and is not intended to limit this specification. Various modifications and variations can be made to this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this specification should be included within the scope of the claims of this specification.

Claims

1. A collision detection method, characterized in that, The method is applied to a C-arm imaging device, wherein image acquisition devices are disposed at a first designated position and a second designated position on the inner surface of the C-arm imaging device, the first designated position and the second designated position being located on both sides of the midpoint of the arc length of the inner surface of the C-arm imaging device, and the method includes: Get a collision detection request; Based on the collision detection request, the initial detection angle and the termination detection angle of the C-arm imaging device are determined, and image data of a specified spatial area are acquired by each image acquisition device as reference image data. The specified spatial area contains at least one target object. Based on the reference image data, a target three-dimensional environment model is constructed, which includes a three-dimensional representation of the C-arm imaging device and the target object. Based on the target 3D environment model, the collision detection results of the C-arm imaging device during its operation from the initial detection angle to the final detection angle are determined, and the collision detection results are displayed to the user. The collision detection results are used to reflect whether the C-arm imaging device will collide during operation.

2. The method as described in claim 1, characterized in that, Based on the reference image data, a target 3D environment model is constructed, specifically including: Each reference image data is detected to determine each feature point contained in each reference image data; For each feature point, the disparity map corresponding to each reference image data is determined based on the displacement of the feature point between its positions in different reference image data. Based on the positional relationship between the image acquisition devices and the disparity map, a target 3D environment model is constructed.

3. The method as described in claim 1, characterized in that, The inner surface of the C-arm imaging device is also provided with at least one other image acquisition device; Image data of a specified spatial region is acquired through various image acquisition devices and used as reference image data, specifically including: Image data of a specified spatial region is acquired using the image acquisition device and other image acquisition devices, and used as reference image data. Based on the reference image data, a target 3D environment model is constructed, specifically including: Each reference image data is detected to determine each feature point contained in each reference image data; For each pair of reference image data, a disparity map corresponding to each pair of reference image data is determined based on the displacement between the positions of each feature point in each pair of reference image data, and this map is used as a reference disparity map. The disparity maps of each reference image are fused to obtain the disparity map corresponding to each reference image data. Based on the positional relationship between each image acquisition device and the disparity map, a target three-dimensional environment model is constructed.

4. The method as described in claim 2 or 3, characterized in that, Based on the positional relationships between the image acquisition devices and the disparity map, a target 3D environment model is constructed, specifically including: Based on the positional relationship between the image acquisition devices and the disparity map, the distance between each feature point in the reference image data and the C-arm imaging device is determined. Based on the distance, a depth map of the specified spatial region is determined, and a target three-dimensional environment model is constructed based on the depth map and the positional relationship between the image acquisition devices.

5. The method as described in claim 1, characterized in that, Displaying the collision detection results to the user specifically includes: If, based on the collision detection results, it is determined that the C-arm imaging device will collide with a target object contained within the specified spatial area during operation, then the target object that collides with the C-arm imaging device is identified as the target object to be marked. In the target 3D environment model, the target object to be marked is marked to obtain the marked target 3D environment model, and the marked target 3D environment model is displayed to the user.

6. The method as described in claim 1, characterized in that, The C-arm imaging device has grooves at both the first and second designated positions, and the image acquisition device is disposed in the grooves. The openings of the grooves are sealed with transparent material.

7. A collision detection device, characterized in that, The apparatus is used to operate a collision detection method applied to a C-arm imaging device. Image acquisition devices are disposed at a first designated position and a second designated position on the inner surface of the C-arm imaging device. The first designated position and the second designated position are respectively located on both sides of the midpoint of the arc length of the inner surface of the C-arm imaging device. The apparatus includes: The receiving module is used to acquire collision detection requests; The determination module is used to determine the initial detection angle and the termination detection angle of the C-arm imaging device according to the collision detection request, and to collect image data of a specified spatial area through each image acquisition device as reference image data, wherein the specified spatial area contains at least one target object; The construction module is used to construct a target three-dimensional environment model based on the reference image data, wherein the target three-dimensional environment model includes a three-dimensional representation of the C-arm imaging device and the target object; The detection module is used to determine the collision detection results of the C-arm imaging device during its operation from the initial detection angle to the final detection angle based on the target three-dimensional environment model, and to display the collision detection results to the user. The collision detection results are used to reflect whether the C-arm imaging device will collide during operation.

8. The apparatus as claimed in claim 7, characterized in that, The construction module is specifically used to detect each reference image data to determine each feature point contained in each reference image data; for each feature point, determine the disparity map corresponding to each reference image data based on the displacement between the positions of the feature point in different reference image data; and construct a target three-dimensional environment model based on the positional relationship between each image acquisition device and the disparity map.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the method described in any one of claims 1 to 6.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method described in any one of claims 1 to 6.

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