Intelligent operating room image direction adaptive matching method and device based on UWB positioning

Abstract

The application provides a smart operating room image orientation adaptive matching method and device based on UWB positioning, which comprises the following steps: identifying the spatial positions of each to-be-identified target in the smart operating room through a plurality of UWB label units; collecting the spatial position data of each to-be-identified target through the time difference algorithm according to the positioning information sent by each UWB label unit; calculating the real-time three-dimensional coordinates of the to-be-identified target by using the spatial position data of the to-be-identified target; establishing the real-time mapping relationship between the world coordinate system and the image coordinate system of the smart operating room based on the real-time three-dimensional coordinates of the to-be-identified target, and generating image adjustment parameters; and converting the image adjustment parameters into orientation control instructions to drive the image equipment to dynamically adjust the orientation of the displayed patient image. The application realizes the real-time and accurate positioning of multiple targets in the operating room through the UWB positioning technology, and realizes the dynamic matching of the image orientation and the operating site by combining the spatial mapping and the image driving logic.

Description

Technical Field

[0001] This invention relates to the field of medical equipment technology, and more particularly to a smart operating room image orientation adaptive matching method and device based on UWB positioning. Background Technology

[0002] With the intelligent development of medical technology, smart operating rooms have become the mainstream clinical surgical scenario. They widely integrate various computer equipment such as imaging workstations, surgical robots, surgical navigation systems, and image AI processing software to present patients' CT, MRI, ultrasound and other medical images in real time during surgery, providing doctors with accurate anatomical structural references for surgical operations, and are the core support for ensuring the safety and effectiveness of surgery.

[0003] In actual surgery, doctors need to move around the operating table and operate various surgical instruments to approach the patient's surgical site according to the needs of the operation. However, in current technology, the patient images displayed by various devices in the operating room are mostly in a pre-set fixed mode, which cannot adaptively adjust to the dynamic changes in the surgical scene. This has the following prominent technical defects, and there is currently no mature solution to effectively solve the following problems: 1. Fixed image display position, lacking dynamic adaptation capability; 2. The image and the patient's position are prone to misalignment, posing a surgical safety hazard; 3. Lack of multi-target spatial linkage mechanism; 4. Poor adaptability of existing positioning technology. Summary of the Invention

[0004] The purpose of this invention is to provide a UWB-based intelligent operating room image orientation adaptive matching method and device to solve the technical problems in existing intelligent operating rooms where the image display orientation is fixed, cannot be linked in real time with the doctor's position, surgical instrument position, and patient position, and is prone to orientation misalignment, increasing surgical risks.

[0005] The technical solution provided by this invention is as follows: In a first aspect, the present invention provides a smart operating room image orientation adaptive matching device based on UWB positioning, comprising: The UWB tag unit includes multiple UWB tags respectively configured in each target to be identified in the smart operating room, used to identify the spatial location of the target to be identified; The UWB positioning subnet includes multiple UWB base stations deployed in the smart operating room, used to receive positioning information sent by each UWB tag unit and collect spatial location data of each target to be identified through a time difference algorithm. The coordinate calculation unit is communicatively connected to the UWB positioning subnet and is used to receive the spatial location data of the target to be identified and calculate the real-time three-dimensional coordinates of the target to be identified. The spatial mapping unit is communicatively connected to the coordinate solving unit and is used to establish a real-time mapping relationship between the world coordinate system and the image coordinate system of the smart operating room based on the real-time three-dimensional coordinates of the target to be identified, and to generate image adjustment parameters. The image driving unit is communicatively connected to the spatial mapping unit and the imaging equipment in the smart operating room, respectively. It is used to receive the image adjustment parameters and convert the image adjustment parameters into orientation control commands to drive the imaging equipment to dynamically adjust the orientation of the displayed patient image.

[0006] In some implementations, the spatial mapping unit further includes: The initial mapping subunit is used to bind the anatomical reference points of the patient image to the spatial coordinates of the patient's UWB tag unit, thereby completing the initial mapping between the image coordinate system and the world coordinate system of the smart operating room.

[0007] In some implementations, the spatial mapping unit further includes: The real-time mapping subunit is used to calculate the relative pose relationship between the targets to be identified based on their real-time three-dimensional coordinates.

[0008] In some implementations, the image orientation transformation matrix is ​​calculated using the following formula: ; in, Let i be the world coordinate system of the intelligent operating room; i, j, and k are the voxel coordinates of the patient image. , , These represent the pixel spacing in the x, y, and z directions, respectively. , , The coordinates of the pixels in the world coordinate system of the smart operating room when the patient image is acquired.

[0009] In some implementations, the spatial mapping unit further includes: The orientation matrix subunit is used to dynamically update the image orientation transformation matrix according to the relative pose relationship between each of the targets to be identified; generate image adjustment parameters based on the image orientation transformation matrix, and transmit the image adjustment parameters to the image driving unit.

[0010] Secondly, the present invention provides a smart operating room image orientation adaptive matching method based on UWB positioning, comprising: The spatial location of each target to be identified in the smart operating room is identified by multiple UWB tag units; Based on the positioning information sent by each UWB tag unit, spatial location data of each target to be identified is collected using a time difference algorithm; Using the spatial location data of the target to be identified, the real-time three-dimensional coordinates of the target to be identified are calculated; Based on the real-time three-dimensional coordinates of the target to be identified, a real-time mapping relationship between the world coordinate system and the image coordinate system of the smart operating room is established, and image adjustment parameters are generated. The image adjustment parameters are converted into orientation control commands to drive the imaging device to dynamically adjust the orientation of the displayed patient image.

[0011] In some implementations, it also includes: The anatomical reference points of the patient image are bound to the spatial coordinates of the patient's UWB tag unit, thus completing the initial mapping between the image coordinate system and the world coordinate system of the smart operating room.

[0012] In some implementations, it also includes: The relative pose relationship between the targets to be identified is calculated based on their real-time three-dimensional coordinates.

[0013] In some implementations, the image orientation transformation matrix is ​​calculated using the following formula: ; in, Let i be the world coordinate system of the intelligent operating room; i, j, and k are the voxel coordinates of the patient image. , , These represent the pixel spacing in the x, y, and z directions, respectively. , , The coordinates of the pixels in the world coordinate system of the smart operating room when the patient image is acquired.

[0014] In some implementations, it also includes: The image orientation transformation matrix is ​​dynamically updated based on the relative pose relationships between the targets to be identified. Based on the image orientation transformation matrix, image adjustment parameters are generated.

[0015] This invention achieves real-time and accurate positioning of multiple targets in the operating room through UWB positioning technology, and combines spatial mapping and image-driven logic to achieve dynamic matching of image orientation with the surgical site. Attached Figure Description

[0016] The preferred embodiments will be described below in a clear and easy-to-understand manner, with reference to the accompanying drawings, to further explain the above-mentioned characteristics, technical features, advantages, and implementation methods of a smart operating room image orientation adaptive matching method and device based on UWB positioning.

[0017] Figure 1 This is a schematic diagram of an embodiment of a smart operating room image orientation adaptive matching device based on UWB positioning according to the present invention; Figure 2 This is a schematic diagram of an embodiment of a smart operating room image orientation adaptive matching device based on UWB positioning according to the present invention; Figure 3 This is a schematic diagram of the layout and orientation matching of the intelligent operating room of the present invention; Figure 4 This is a schematic diagram of an embodiment of an intelligent operating room image orientation adaptive matching method based on UWB positioning according to the present invention. Detailed Implementation

[0018] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application can also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0019] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or sets.

[0020] To keep the drawings concise, only the parts relevant to the invention are shown schematically in each figure, and they do not represent the actual structure of the product. Furthermore, for ease of understanding, in some figures, only one of components with the same structure or function is shown schematically, or only one is labeled. In this document, "one" can mean not only "only one" but also "more than one".

[0021] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0022] Furthermore, in the description of this application, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the specific implementation methods of the present invention will be described below with reference to the accompanying drawings. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings and other implementation methods can be obtained based on these drawings without any creative effort.

[0024] Unless otherwise defined, all technical and scientific terms used in the embodiments of this application have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in the embodiments of this application is for descriptive purposes only and is not intended to limit the application. Before further detailed description of the embodiments of this application, the nouns and terms involved in the embodiments of this application are explained, and the nouns and terms involved in the embodiments of this application are subject to the following interpretations.

[0025] In existing technologies, the patient images displayed by various devices in the operating room are mostly in a pre-set, fixed orientation, which cannot adaptively adjust to the dynamic changes in the surgical environment. This presents the following prominent technical defects, and currently there is no mature solution that can effectively solve the following problems: 1. Fixed image display orientation, lacking dynamic adaptation capability: The current image display orientation is preset based on the patient's initial position before surgery. It cannot be adjusted in real time according to changes in the doctor's standing position, the posture of the operating table (such as raising, lowering, tilting), and the position of surgical instruments. This causes doctors to frequently switch between "image orientation and on-site orientation" in their minds when observing the screen, increasing cognitive load and making it easy to misjudge the orientation.

[0026] 2. Imaging and patient positioning are prone to misalignment, posing a surgical safety hazard: When the doctor changes the surgical position (such as switching from the patient's left side to the right side) or the operating table is adjusted, the left-right and front-back positions of the patient's image on the screen are prone to being reversed from the patient's actual position. Especially in minimally invasive surgery and precision navigation surgery, misalignment may lead to misoperation of surgical instruments and cause medical risks.

[0027] 3. Lack of multi-target spatial linkage mechanism: The existing technology has not established a real-time spatial linkage relationship between "doctor, surgical instruments, patient display device" and "patient display device". The patient image orientation displayed by different devices (such as surgical robot and imaging workstation) may be inconsistent, which will cause confusion in the doctor's operation and affect the efficiency of the operation.

[0028] 4. Poor adaptability of existing positioning technologies: The optical and electromagnetic positioning technologies commonly used in operating rooms have problems such as being easily interfered with by surgical instruments and obstructions, insufficient positioning accuracy (above millimeter level), complex wiring, and high response latency (greater than 100ms), which cannot meet the positioning requirements of multi-target, dynamic, high-precision, and low-latency in surgical scenarios.

[0029] To address the above problems, this invention provides a technical solution that enables real-time multi-target positioning in the surgical field, drives adaptive image orientation matching, and offers reliable positioning with strong compatibility, thus solving the current technical challenges in the field of smart operating rooms.

[0030] This invention achieves real-time, precise positioning of multiple targets within the operating room using UWB positioning technology. Combined with spatial mapping and image-driven logic, it enables dynamic matching of image orientation with the surgical environment. The device employs a modular design, with each unit working collaboratively to achieve a closed-loop process encompassing positioning, calculation, mapping, and driving. (See reference...) Figure 1 The diagram shows a smart operating room image orientation adaptive matching device based on UWB positioning. The specific components of this device are as follows: UWB tag unit 101 includes multiple UWB tags respectively configured on each target to be identified in the smart operating room, used to identify the spatial location of the target. UWB positioning subnet 102 includes multiple UWB base stations deployed in the smart operating room, used to receive positioning information sent by each UWB tag unit and collect spatial location data of each target using a time difference of arrival (TDOA) algorithm. Coordinate calculation unit 103, communicatively connected to the UWB positioning subnet, is used to receive the spatial location data of the target and calculate the real-time three-dimensional coordinates of the target. Spatial mapping unit 104, communicatively connected to the coordinate calculation unit, is used to establish a real-time mapping relationship between the world coordinate system and the image coordinate system of the smart operating room based on the real-time three-dimensional coordinates of the target, and generate image adjustment parameters. Image driving unit 105, communicatively connected to the spatial mapping unit and the imaging equipment in the smart operating room, is used to receive the image adjustment parameters and convert them into orientation control commands to drive the imaging equipment to dynamically adjust the orientation of the displayed patient image.

[0031] The UWB positioning subnet is the core positioning component in the device of this invention. (See reference...) Figure 2The diagram shows a smart operating room image orientation adaptive matching device based on UWB positioning. Its deployment is as follows: 4-6 UWB base stations are deployed at the four corners and center of the top of the smart operating room, with a spacing of 2-3 meters between each UWB base station to ensure no positioning blind spots in the surgical area (operating table and surrounding 1.5 meters). The UWB base stations are fixed to ceiling supports at a height of 2.8-3.2 meters to avoid obstruction by surgical instruments. Its hardware parameters include: the UWB base stations use ultra-wideband pulse radio (IRUWB) technology, operating in the 3.1-10.6 GHz frequency band, with a positioning accuracy ≤10cm, a positioning refresh rate of 50-100Hz, a response latency ≤50ms, support for simultaneous positioning of multiple tags (up to 30 tags), anti-multipath interference and anti-obstruction capabilities, PoE power supply, and support for TCP / IP communication. The UWB positioning subnet is used to receive positioning signals sent by each UWB tag, collect spatial location data of the tags through the Time Difference of Arrival (TDoA) algorithm, and transmit it to the coordinate calculation unit.

[0032] For reference Figure 3 The diagram shows the layout and orientation matching of the smart operating room. The UWB tag unit of this invention serves as a positioning identification component, marking the spatial location of each target to be identified. The targets to be identified in this invention include the patient (1), doctor (2), surgical instruments (3), display terminal (4), etc., in the smart operating room. Since there are various types of targets to be identified, in order to achieve adaptive matching of various precision and real-time in the smart operating room, different types of UWB tags are configured for different targets to be identified in this invention, and different types of spatial location data are identified.

[0033] Specifically, the label classification and configuration include: Patient UWB tags: Small patch-type tags are fixed to reference points on the patient's body surface (such as the midline of the sternum, the anterior superior iliac spine) or the armrests on both sides of the operating table (fixed to the patient's position) to identify the spatial position and posture of the patient and the operating table.

[0034] UWB tags for surgical instruments: These are integrated tags embedded inside the handles of surgical instruments (such as laparoscopes, ultrasound probes, and surgical robot end effectors) to meet the sterilization requirements of surgical instruments and to identify the real-time location and orientation of the instruments.

[0035] UWB tags for doctors: Wearable tags (such as wristbands or chest pendants) that are rechargeable are used to identify the doctor's real-time position and body orientation.

[0036] UWB tags for display terminals: These are fixed to the surface of devices such as the screen bezel of an imaging workstation and the display panel of a surgical robot, and are aligned with the center of the display area of ​​the screen to identify the spatial location and orientation of the display device.

[0037] The UWB tag parameters include: operating frequency band consistent with UWB base station (e.g., operating frequency band is 3.1~10.6GHz), transmission power ≤10mW, positioning refresh rate synchronized with UWB base station (e.g., positioning refresh rate is 50~100Hz), communication distance ≥10m, low power consumption design, and support for sleep / wake-up (e.g., automatic sleep when idle, wake-up when close to UWB base station).

[0038] This invention proposes an image orientation matching scheme based on "UWB global positioning and multi-target linkage," deeply integrating UWB positioning technology with smart operating room image display to achieve real-time spatial linkage among doctors, surgical instruments, patients, and display terminals. This solves the core pain point of existing technologies, which suffer from fixed image orientation and inability to dynamically adapt. Compared to existing optical and electromagnetic positioning technologies, UWB positioning technology offers stronger resistance to occlusion and multipath interference, adapting to the complex environment of operating rooms with dense instruments and frequent personnel movement. It provides stable positioning accuracy (≤10cm) and low response latency (≤50ms), ensuring the real-time performance and stability of image adjustments.

[0039] In this invention, the coordinate calculation unit serves as the core computing component. Its hardware configuration utilizes an industrial-grade embedded processor (such as an Intel Core i7 12700H), supporting real-time computation and data caching, possessing anti-electromagnetic interference capabilities, and adapting to the operating room medical equipment environment. The interface supports TCP / IP and RS485 serial communication, enabling data interaction with the UWB base station and spatial mapping unit, transmitting the calculated coordinate data. The coordinate calculation unit also incorporates a TDoA positioning algorithm and an attitude calculation algorithm. It receives the raw tag data transmitted from the UWB base station, calculates the three-dimensional coordinates (X, Y, Z axes, establishing a world coordinate system with the operating table center as the origin) of each tag, and its data update frequency is synchronized with the UWB base station. Simultaneously, it filters abnormal positioning data (such as jumps caused by occlusion) using a Kalman filter algorithm to ensure the stability and accuracy of the positioning data.

[0040] Because each UWB tag is attached to a device or human body in a smart operating room, such as a patient, doctor, robotic arm of a surgical robot, imaging equipment, or movable bed board of an operating table, the tags will shift at any time during the operation. This invention collects and updates the data returned by the tags at a certain frequency to calculate the real-time position of each component in the coordinate system defined by this invention, so as to avoid the problem of inaccurate real-time three-dimensional coordinates caused by the displacement of UWB tags.

[0041] The TDoA positioning algorithm and attitude calculation algorithm rely on UWB technology to obtain the coordinates (X, Y, Z coordinates, tag ID, and timestamp) of the tags between UWB base stations. Based on the coordinate information returned by the UWB tags and each tag ID, the position of the newly calibrated coordinate system in the smart operating room space used in this invention is calculated. This new coordinate system differs from commercial UWB base stations; during deployment, a proprietary spatial coordinate system is provided, such as a new coordinate system with the origin defined by the operating table head or imaging equipment markers. The coordinates of each tag in the UWB base station are converted into the coordinates of this system according to the initial installation and calibration information.

[0042] In this invention, the spatial mapping unit serves as an orientation transformation component. Its core function is to establish a real-time mapping relationship between the "operating room world coordinate system" and the "image coordinate system," generating an image orientation transformation matrix (including rotation and translation matrices) to achieve a precise correspondence between spatial coordinates and image coordinates. Built-in spatial coordinate transformation and relative pose calculation algorithms ensure real-time image adjustment with a computational latency of ≤30ms.

[0043] The spatial mapping unit includes an initial mapping subunit, used to bind the anatomical reference points of the patient image to the spatial coordinates of the patient's UWB tag unit, completing the initial mapping between the image coordinate system and the world coordinate system of the smart operating room. This initial mapping subunit specifically includes: binding the anatomical reference points of the patient image (such as the apex of the skull and the pubic symphysis) to the spatial coordinates of the UWB tag on the patient's body surface through preoperative calibration, completing the initial registration of the image coordinate system and the world coordinate system of the smart operating room.

[0044] This embodiment establishes a unified spatial coordinate system for the operating room and constructs a world coordinate system for the operating room based on the operating table. This enables real-time calculation of the three-dimensional coordinates and attitude angles of multiple targets such as doctors, surgical instruments, patients, and display terminals, unifies the spatial positioning reference of each device, and solves the problem of inconsistent image display across multiple devices.

[0045] Since different targets to be identified will move or change spatially when used in a smart operating room, in order to make adaptive matching more timely, the spatial mapping unit of the present invention further includes: a real-time mapping subunit, used to calculate the relative pose relationship between the targets to be identified based on the real-time three-dimensional coordinates of each target to be identified.

[0046] Specifically, based on the real-time coordinates and attitude angles of the doctor, instruments, patient, and display terminal output by the coordinate calculation unit, the relative pose relationship between the four is calculated, and the transformation matrix is ​​dynamically updated. For example, when the doctor's position changes, the image rotation angle is adjusted to ensure that the screen image from the doctor's perspective is consistent with the patient's actual position. This achieves adaptive matching of image orientation with the doctor's position. By calculating the relative position of the doctor and patient in real time, the image rotation and mirror angle are automatically adjusted without requiring the doctor to manually switch perspectives, reducing the doctor's cognitive load and operational steps, and improving surgical efficiency. This is different from existing technical solutions that require manual adjustment of image orientation.

[0047] This embodiment achieves real-time consistency between the orientation of the screen image and the surgical site, ensuring that the left-right, front-back, and up-down orientation of the patient image displayed by the imaging workstation, surgical robot, navigation software, and other devices accurately corresponds to the patient's actual position on the operating table, the doctor's current position, and the actual position of the surgical instruments, realizing "what you see is what you are" and eliminating the risk of orientation misalignment.

[0048] Once the world coordinate system of the smart operating room is established, the initial positions of each UWB tag can be calculated. First, when the imaging equipment acquires patient images, the patient's position information is stored in the DICOM image tag through the patient's position settings on the imaging equipment. When the patient's position information is displayed on the image playback device, the patient's position on the screen can be adjusted according to the patient's position information, such as up, down, left, and right.

[0049] When surgical instruments approach the patient, the system automatically zooms in on a local area of ​​the image and marks the corresponding position of the instruments on the image. The standard method is to use a colored arrow in the software and highlight the corresponding position with text.

[0050] In the initial mapping step, the UWB tags bound to the patient's anatomical reference points have a spatial coordinate relationship at the time of image acquisition. After being recorded by the system, this relationship is transformed through mapping, allowing the system to read and convert information such as the patient's orientation and position in the image. Devices used to display the images, such as imaging workstations or surgical robot control equipment, also have UWB positioning tags that provide coordinate information. Through the initial registration algorithm, the relative positions of each tag are calculated, converting the spatial relationship of the patient image viewed by the patient and doctor into the relative spatial relationship of the patient presented by the imaging device, reflecting the relative relationships of the real-world environment.

[0051] In addition, when establishing the spatial coordinate system of the smart operating room, the ID and attributes of each UWB tag are set. For surgical instrument types, for example, the type is set to TYPE_OPERATION_ARM, which has an application scenario close to the patient in a real-world setting. In this way, when the coordinates returned by the UWB tag bound to the surgical instrument are detected by the system as being close to the patient, the local area of ​​the image and the corresponding position can be automatically scaled.

[0052] The image driving unit of this invention, as an execution component, functions to receive the transformation matrix output by the spatial mapping unit, output orientation control commands to devices such as image workstations, surgical robots, navigation software, and image AI processing software, and drive the devices to perform image perspective adjustment operations. Its interface is compatible, supporting multiple mainstream interfaces and protocols, including TCP / IP, SDK development interfaces, and the DICOM protocol (medical imaging standard protocol). It can directly interface with existing image workstations, surgical robots, navigation software, and image AI processing systems without requiring large-scale modifications to existing operating room equipment, reducing hospital investment costs. It can be widely applied to various smart operating rooms (such as general operating rooms, orthopedic operating rooms, and neurosurgical operating rooms), exhibiting strong compatibility and wide adaptability.

[0053] This embodiment constructs a unified spatial coordinate system for the operating room and establishes a real-time dynamic mapping mechanism of "world coordinate system → image coordinate system". This solves the problem of inconsistent image display orientations of multiple devices (surgical robot, navigation software, image workstation) and achieves unified synchronization of image orientations of multiple devices. It is also highly compatible and can be connected to existing mainstream medical equipment without large-scale modifications.

[0054] In addition, to make the use of smart operating rooms more flexible, the device of this invention supports two modes: automatic adjustment and manual locking. In automatic mode, the image orientation is adjusted in real time according to positioning data. In manual mode, doctors can lock the current image view through the surgical console or foot switch to adapt to specific surgical operation needs. At the same time, it supports saving doctors' preferences, which can record the standing habits of different doctors and automatically match the corresponding image view.

[0055] This invention features a low-latency, highly stable positioning and driving logic. It optimizes positioning data using a Kalman filter algorithm, ensuring a positioning accuracy of ≤10cm and a response latency of ≤50ms. The image adjustment is highly real-time, and it supports saving doctor preferences and switching between automatic and manual modes, adapting to different surgical scenarios and doctor operating habits, making it highly practical. For example, it can adjust image adaptation parameters according to different surgical types and different doctor operating habits. It can also automatically scale local areas of the image based on the distance between surgical instruments and the patient, providing doctors with clearer and more realistic image references.

[0056] In some embodiments, the spatial mapping unit further includes: an orientation matrix subunit, configured to dynamically update the image orientation transformation matrix according to the relative pose relationship between each of the targets to be identified; generate image adjustment parameters based on the image orientation transformation matrix; and transmit the image adjustment parameters to the image driving unit.

[0057] The formula for calculating the image orientation transformation matrix is ​​as follows: ; in, Let i be the world coordinate system of the intelligent operating room; i, j, and k are the voxel coordinates of the patient image. , , These represent the pixel spacing in the x, y, and z directions, respectively. , , The coordinates of the pixels in the world coordinate system of the smart operating room when the patient image is acquired.

[0058] Specifically, the spatial mapping unit dynamically updates the transformation matrix of "world coordinate system → image coordinate system" based on the relative pose relationship, and generates image adjustment parameters, including: rotation angle (adjusted according to the doctor's position, range 0~360°), mirror mode (switched left and right according to the doctor's position), translation distance (adjusted according to the position of the display terminal), and scaling ratio (adjusted according to the distance between the instrument and the patient, range 0.5~2.0 times).

[0059] The spatial mapping unit of this invention binds the anatomical reference points of the patient image to the patient's label coordinates through preoperative calibration, completing the initial registration; during the operation, it dynamically updates the transformation matrix according to the real-time pose of each target, generating image rotation, mirroring, translation, and scaling parameters to achieve precise matching between image orientation and on-site location.

[0060] This invention belongs to the field of smart operating room technology, specifically involving surgical navigation, medical image display and spatial positioning fusion technology. The following describes in detail how the device of this invention can be applied to the actual use of smart operating rooms.

[0061] The workflow of this device consists of five steps: initial calibration, real-time positioning, pose calculation, orientation mapping, and image refresh. These steps form a closed loop to ensure that the image orientation matches the surgical site in real time. The specific steps are as follows: 1. Initial calibration (preoperative preparation, time ≤ 5 minutes) Step 1.1: The UWB base station is started, completes self-test and networking, and ensures that each base station communicates normally and that there are no blind spots in positioning coverage; all UWB tags are powered on, paired with the base station, and enter the positioning ready state.

[0062] Step 1.2: Place the patient in the preset position on the operating table, fix the patient tag to the patient's body surface reference point, adjust the operating table to the preset surgical posture (e.g., supine or lateral), and record the initial three-dimensional coordinates of the operating table and the patient (with the center of the operating table as the origin, the X-axis representing the patient's left and right direction, the Y-axis representing the patient's head and feet direction, and the Z-axis representing the direction perpendicular to the ground). The operating table is generally a third-party device, which can be a portable or motorized operating table. Because a UWB tag has been bound in the previous steps, the orientation and position of the operating table can be detected by the system. The specific orientation of the operating table can be specified by the user, and all will ultimately be loaded into the spatial calculation unit.

[0063] Recording initial 3D coordinates: According to the DICOM specification, the patient's orientation in the image is recorded using tag information within DICOM, such as HFS, which reflects the patient's actual orientation in the image coordinate system. Because the patient's anatomical reference point is bound to a UWB tag, the coordinates of the UWB tag are recorded during patient image acquisition, and the transformation matrix can be obtained using a spatial transformation formula.

[0064] Step 1.3: Import the patient's preoperative CT / MRI / ultrasound images into the imaging workstation, select 35 anatomical reference points in the images (corresponding to the patient's surface label positions), complete the initial registration of the image coordinate system and the operating room world coordinate system, generate the initial transformation matrix, and save it to the spatial mapping unit.

[0065] Step 1.4: The doctor puts on the doctor tag, holds the surgical instruments with the tag, and stands in a preset position around the operating table (such as the left, right, or head of the patient). The system records the doctor's coordinates and image adaptation parameters at different positions to complete the doctor preference initialization.

[0066] 2. Real-time positioning (continuous operation during surgery) The UWB base station continuously receives positioning signals from various UWB tags (patients / operating tables, instruments, doctors, display terminals), acquiring raw signal data every 50-100Hz and transmitting it to the coordinate calculation unit via communication to ensure the real-time nature of the positioning data. This acquisition frequency is primarily to meet the refresh rate requirements for image display, preventing lag in tag location information updates that could affect trial performance. Users can adjust this frequency according to their actual engineering needs.

[0067] 3. Relative pose calculation (performed simultaneously with localization) The coordinate calculation unit calculates the received raw positioning data and outputs the real-time three-dimensional coordinates of each tag (accuracy ≤10cm). After filtering out abnormal data, it transmits the data to the spatial mapping unit.

[0068] The spatial mapping unit calculates the relative positional relationship of the four components based on the solution data: ① the relative position of the doctor and the patient (e.g., the doctor is located 30cm to the left of the patient); ② the relative distance between the surgical instruments and the surgical site of the patient (accuracy ≤ 5cm); ③ the relative orientation of the display terminal and the doctor; ④ the changes in the posture of the operating table (e.g., tilt angle, height adjustment).

[0069] 4. Azimuth matrix generation (real-time calculation) The spatial mapping unit dynamically updates the transformation matrix of "world coordinate system → image coordinate system" based on the relative pose relationship, and generates image adjustment parameters, including: rotation angle (adjusted according to the doctor's position, range 0~360°), mirror mode (switched left and right according to the doctor's position), translation distance (adjusted according to the position of the display terminal), and scaling ratio (adjusted according to the distance between the instrument and the patient, range 0.5~2.0 times).

[0070] Once the adjusted parameters are generated, they are immediately transmitted to the image driving unit.

[0071] 5. Dynamic refresh (executed in real time) The image driving unit converts the adjustment parameters into control commands for the corresponding devices, and sends them to devices such as image workstations and surgical robots through the adapter interface, driving the devices to adjust the image display angle in real time.

[0072] When there is no significant change in the position of each target (expected change ≤ 2cm), the system maintains the current image viewpoint and reduces unnecessary refreshes; when the position change is > 2cm, the system immediately triggers an image refresh to ensure that the image orientation is always consistent with the on-site position.

[0073] This embodiment enables adaptive adjustment of image orientation. Based on changes in the doctor's position, the distance between surgical instruments and the patient, and the adjustment of the operating table posture, the imaging software is automatically driven to perform orientation correction operations such as viewpoint rotation, mirroring, translation, and zooming, without requiring manual switching by the doctor, thus reducing the operational burden.

[0074] The device and method of the present invention enable doctors to switch to manual mode via a foot switch or console during surgery to lock the current image viewpoint as needed, and switch back to automatic mode after the operation is completed to restore adaptive adjustment.

[0075] By combining automatic and manual execution modes, the surgical experience and safety are optimized. By reducing the cognitive load of doctors changing positions, the risk of misoperation is reduced, and the intuitiveness and efficiency of surgical operations are improved, providing reliable technical support for precision and minimally invasive surgery.

[0076] Based on the above device, refer to as follows Figure 4The flowchart illustrates a method for adaptive image orientation matching in a smart operating room based on UWB positioning. The method includes: S101 identifying the spatial location of each target to be identified in the smart operating room using multiple UWB tag units; S102 collecting spatial location data of each target to be identified using a time-difference-of-arrival (TDOA) algorithm based on the positioning information sent by each UWB tag unit; S103 calculating the real-time three-dimensional coordinates of the target to be identified using the spatial location data; S104 establishing a real-time mapping relationship between the world coordinate system and the image coordinate system of the smart operating room based on the real-time three-dimensional coordinates of the target to be identified, generating image adjustment parameters; and S105 converting the image adjustment parameters into orientation control commands to drive the imaging equipment to dynamically adjust the orientation of the displayed patient image.

[0077] Specifically, the initial calibration involves: activating the UWB base station, UWB tags, and all units to complete UWB base station networking and tag pairing; placing the patient in a preset position on the operating table and fixing the patient tag; importing the patient's preoperative images into the imaging equipment, selecting anatomical reference points for the images, and binding them to the patient tag coordinates to complete the initial registration of the image coordinate system with the world coordinate system; recording the image adaptation parameters for the doctor's preset position and saving the doctor's preferences. Real-time positioning: The UWB base station continuously collects positioning signals from each UWB tag and transmits the raw signals to the coordinate calculation unit at a frequency of 50-100Hz. Pose calculation: The coordinate calculation unit uses the TDoA positioning algorithm and Kalman filter algorithm to calculate the three-dimensional coordinates and attitude angles of each UWB tag, filters out abnormal data, and transmits the calculation results to the spatial mapping unit. Orientation mapping: Based on the calculation results, the spatial mapping unit calculates the relative pose relationships of the doctor, surgical instruments, patient, and display terminal, dynamically updates the image orientation transformation matrix, and generates image adjustment parameters. Dynamic refresh: The image driving unit converts image adjustment parameters into control commands and sends them to the imaging device to drive the imaging device to adjust the image display orientation in real time, ensuring that the image orientation is consistent with the actual position of the surgical site; when the change in each target position is ≤2cm, the current image view is maintained; when the change is >2cm, the image refresh is triggered.

[0078] In this embodiment, the doctor can switch to manual mode via a foot switch or console to lock the current image viewpoint; after the operation is completed, switch back to automatic mode to restore the adaptive adjustment of the image orientation.

[0079] This invention promotes the intelligent upgrade of smart operating rooms, realizes the deep integration of positioning technology and image display technology, improves the spatial linkage capability of smart operating rooms, and provides basic support for subsequent intelligent functions such as collaborative operation of surgical robots and intraoperative AI navigation. It has broad application prospects and promotional value.

[0080] When this invention is applied to real-world scenarios, the specific software flow and operation steps include: 1. Preoperative preparation steps (operated by: operating room nurse / doctor) Step 1: Start the system and turn on the UWB base station, UWB tag, coordinate calculation unit, spatial mapping unit, image driving unit and each image device in sequence. Check the communication status of each unit through the host computer software to ensure there are no faults.

[0081] Step 2: Place the patient in the pre-set supine position on the operating table, adjust the height of the operating table (about 70cm), and use medical tape to fix the patient tag to the midline of the patient's sternum, ensuring that the tag fits the skin and is not loose.

[0082] Step 3: Import the patient's preoperative CT images (DICOM format) into the imaging workstation, select 3 anatomical reference points (skull vertex, pubic symphysis, and midpoint of the sternal midline), input the patient label coordinates corresponding to these 3 reference points in the spatial mapping software, complete the initial registration of the image coordinate system and the world coordinate system, generate the initial transformation matrix, and save the parameters.

[0083] Step 4: The doctor puts on the wrist tag, holds the laparoscope with the tag, and stands in three preset positions: left, right and head of the patient. The system automatically records the doctor's coordinates and image adaptation parameters at each position and saves the doctor's preference settings (e.g., if the doctor is used to standing on the left, the image will default to displaying the patient's left side view).

[0084] Step 5: Switch the system to automatic mode, check whether the image display is consistent with the patient's actual position, and whether the image can be adjusted synchronously when the surgical instruments are moved. After confirming that the system is normal, prepare for surgery.

[0085] 2. Intraoperative procedures (automatic operation by the system, with manual intervention possible by the physician) Step 1: The UWB base station continuously receives signals from each tag, collects raw data every 80Hz, and transmits it to the coordinate calculation unit. The calculation unit filters out abnormal data using the Kalman filter algorithm and outputs the real-time three-dimensional coordinates of each tag (e.g., doctor's coordinates: X=150cm, Y=200cm, Z=180cm).

[0086] Step 2: The spatial mapping unit calculates the relative position of the doctor and the patient (e.g., the doctor is 25cm to the right of the patient) and the relative distance between the surgical instruments and the surgical site of the patient (e.g., the instruments are 5cm away from the patient's abdomen) based on the solved data, generates an updated transformation matrix, and outputs image adjustment parameters (e.g., rotation angle 90°, mirror mode enabled, scaling ratio 1.2x).

[0087] Step 3: The image driving unit converts the adjustment parameters into control commands and sends them to the image workstation via the DICOM protocol, driving the image workstation to adjust the image viewing angle to ensure that the screen image is consistent with the doctor's position and the instrument position.

[0088] Step 4: When the doctor moves his position (e.g., from the right side of the patient to the left side), the system detects the change in the doctor's label coordinates (change > 2cm), immediately recalculates the relative pose, updates the transformation matrix, drives the image to adjust the viewing angle synchronously, and switches to the patient's left-side view. The whole process does not require manual operation by the doctor.

[0089] Step 5: When performing delicate operations (such as bringing the instrument close to the patient's surgical site), the system detects that the distance between the instrument and the patient is less than 3cm, automatically zooms in on the local area of ​​the image (zoom ratio 1.5 times), and marks the corresponding position of the instrument on the image for easy observation by the doctor; after the operation is completed, the instrument moves away, and the image automatically returns to the normal scale.

[0090] Step 6: If the doctor needs to fix the current image view (such as when performing complex suturing operations), he can switch to manual mode by stepping on the foot switch to lock the current image view; after the operation is completed, step on the foot switch again to switch back to automatic mode and restore adaptive adjustment.

[0091] 3. Postoperative Completion Procedures Step 1: After the surgery, turn off all imaging equipment and surgical instruments, remove the doctor's label, patient's label, and instrument label, turn off the power to the labels, and disinfect them (instrument labels need to be sterilized by high-pressure steam to ensure waterproof performance).

[0092] Step 2: Save the positioning data, image adjustment parameters, and doctor preference settings of this surgery through the host computer software for easy reuse in subsequent surgeries.

[0093] Step 3: Sequentially shut down the image driving unit, spatial mapping unit, coordinate calculation unit, and UWB base station, cut off the system power, and complete the surgical procedure.

[0094] The system applied in this method includes a UWB positioning subnet, UWB tag units, coordinate calculation units, spatial mapping units, and image driving units. UWB base stations are deployed to achieve centimeter-level positioning coverage throughout the operating room. UWB tags are respectively configured on patients, surgical instruments, doctors, and display terminals. After initial calibration and spatial registration, the system captures the three-dimensional coordinates and attitude angles of each target in real time, calculates their relative poses, generates an image orientation transformation matrix, and drives the image workstation, surgical robot, navigation software, and other equipment to dynamically adjust the image display perspective, achieving precise matching between the screen image and the actual orientation of the surgical site. This invention offers high positioning accuracy, resistance to occlusion, rapid response, and strong compatibility, significantly improving the intuitiveness of surgical operations, reducing the risk of orientation misjudgment, and adapting to various smart operating room scenarios.

[0095] It should be noted that the above embodiments can be freely combined as needed. The above description is only a preferred embodiment of the present invention. It should be pointed out that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A smart operating room image orientation adaptive matching device based on UWB positioning, characterized in that, include: The UWB tag unit includes multiple UWB tags respectively configured in each target to be identified in the smart operating room, used to identify the spatial location of the target to be identified; The UWB positioning subnet includes multiple UWB base stations deployed in the smart operating room, used to receive positioning information sent by each UWB tag unit and collect spatial location data of each target to be identified through a time difference algorithm. The coordinate calculation unit is communicatively connected to the UWB positioning subnet and is used to receive the spatial location data of the target to be identified and calculate the real-time three-dimensional coordinates of the target to be identified. The spatial mapping unit is communicatively connected to the coordinate solving unit and is used to establish a real-time mapping relationship between the world coordinate system and the image coordinate system of the smart operating room based on the real-time three-dimensional coordinates of the target to be identified, and to generate image adjustment parameters. The image driving unit is communicatively connected to the spatial mapping unit and the imaging equipment in the smart operating room, respectively. It is used to receive the image adjustment parameters and convert the image adjustment parameters into orientation control commands to drive the imaging equipment to dynamically adjust the orientation of the displayed patient image.

2. The intelligent operating room image orientation adaptive matching device based on UWB positioning according to claim 1, characterized in that, The spatial mapping unit further includes: The initial mapping subunit is used to bind the anatomical reference points of the patient image to the spatial coordinates of the patient's UWB tag unit, thereby completing the initial mapping between the image coordinate system and the world coordinate system of the smart operating room.

3. The intelligent operating room image orientation adaptive matching device based on UWB positioning according to claim 1, characterized in that, The spatial mapping unit further includes: The real-time mapping subunit is used to calculate the relative pose relationship between the targets to be identified based on their real-time three-dimensional coordinates.

4. The intelligent operating room image orientation adaptive matching device based on UWB positioning according to any one of claims 1 to 3, characterized in that, The spatial mapping unit further includes: The orientation matrix subunit is used to dynamically update the image orientation transformation matrix according to the relative pose relationship between each of the targets to be identified; generate image adjustment parameters based on the image orientation transformation matrix, and transmit the image adjustment parameters to the image driving unit.

5. The intelligent operating room image orientation adaptive matching device based on UWB positioning according to claim 4, characterized in that, The formula for calculating the image orientation transformation matrix is ​​as follows: ； in, Let i be the world coordinate system of the intelligent operating room; i, j, and k are the voxel coordinates of the patient image. , , These represent the pixel spacing in the x, y, and z directions, respectively. , , The coordinates of the pixels in the world coordinate system of the smart operating room when the patient image is acquired.

6. A smart operating room image orientation adaptive matching method based on UWB positioning, characterized in that, include: The spatial location of each target to be identified in the smart operating room is identified by multiple UWB tag units; Based on the positioning information sent by each UWB tag unit, spatial location data of each target to be identified is collected using a time difference algorithm; Using the spatial location data of the target to be identified, the real-time three-dimensional coordinates of the target to be identified are calculated; Based on the real-time three-dimensional coordinates of the target to be identified, a real-time mapping relationship between the world coordinate system and the image coordinate system of the smart operating room is established, and image adjustment parameters are generated. The image adjustment parameters are converted into orientation control commands to drive the imaging device to dynamically adjust the orientation of the displayed patient image.

7. The intelligent operating room image orientation adaptive matching method based on UWB positioning according to claim 6, characterized in that, Also includes: The anatomical reference points of the patient image are bound to the spatial coordinates of the patient's UWB tag unit, thus completing the initial mapping between the image coordinate system and the world coordinate system of the smart operating room.

8. The intelligent operating room image orientation adaptive matching method based on UWB positioning according to claim 6, characterized in that, Also includes: The relative pose relationship between the targets to be identified is calculated based on their real-time three-dimensional coordinates.

9. The intelligent operating room image orientation adaptive matching method based on UWB positioning according to any one of claims 6 to 8, characterized in that, Also includes: The image orientation transformation matrix is ​​dynamically updated based on the relative pose relationships between the targets to be identified. Based on the image orientation transformation matrix, image adjustment parameters are generated.

10. The intelligent operating room image orientation adaptive matching method based on UWB positioning according to claim 9, characterized in that, The formula for calculating the image orientation transformation matrix is ​​as follows: ； in, Let i be the world coordinate system of the intelligent operating room; i, j, and k are the voxel coordinates of the patient image. , , These represent the pixel spacing in the x, y, and z directions, respectively. , , The coordinates of the pixels in the world coordinate system of the smart operating room when the patient image is acquired.

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