A method and device for testing the matching accuracy of an inflated lung 3D model with actual lung structures, and an electronic device

Abstract

This invention provides a method, apparatus, and electronic device for testing the accuracy of matching an inflatable lung 3D model with an actual lung structure, relating to the field of medical data analysis and processing technology. The method includes: the system under test automatically registering the inflatable lung 3D model with the actual lung structure based on the test operation sequence to obtain a registration result; wherein the registration result includes the projection coordinates of the simulated marker points in the endoscopic video coordinate system; determining the positional deviation between the projection point coordinates and the corresponding real marker point coordinates based on the registration result; and evaluating the model matching accuracy of the system under test based on the positional deviation. This invention controls the system under test to automatically complete the entire registration process through a predefined test operation sequence, eliminating subjective bias and random errors introduced by manual intervention, making the testing process standardized and the results quantifiable, thus improving the efficiency and objectivity of the evaluation.

Description

Technical Field

[0001] This invention relates to the field of medical data analysis and processing technology, and in particular to a method, device, and electronic device for testing the accuracy of matching an inflatable lung 3D model with the actual lung structure. Background Technology

[0002] With the widespread adoption of thoracoscopic minimally invasive surgery, surgical navigation systems are playing an increasingly important role in precision surgeries such as pulmonary nodule resection. The core function of these systems is to register a preoperative 3D model of the inflated lung reconstructed from CT images with the actual collapsed lung structure captured by intraoperative laparoscopic video, thereby providing surgeons with real-time, precise guidance for locating deep lesions. However, as a non-rigid organ, the lung undergoes complex and non-linear deformation from an inflated state outside the body to a collapsed state during surgery, making high-precision model registration an extremely challenging task. The accuracy of the registration directly determines the reliability of the navigation system and the success rate of the surgery.

[0003] Currently, the evaluation of registration accuracy for such navigation systems largely relies on the surgeon's subjective visual judgment during surgery or simplified experiments based on in vitro phantoms. The former lacks objective, quantitative evaluation indicators and is heavily influenced by personal experience; the latter cannot realistically reproduce the complex physiological environment and deformation processes within the human body. The industry lacks a standard method and tool that can automatically, quantitatively, and systematically evaluate the accuracy of the match between the inflatable lung model and the actual lung structure during surgery. This deficiency not only makes performance comparisons between different systems difficult but also hinders the iterative optimization and standardization of surgical navigation technology itself.

[0004] Therefore, a method, device, and electronic equipment for testing the accuracy of matching an inflatable lung 3D model with the actual lung structure are proposed. Summary of the Invention

[0005] This specification provides a method, device, and electronic equipment for testing the accuracy of matching an inflatable lung 3D model with the actual lung structure. By controlling the system under test to automatically complete the entire registration process through a predefined test operation sequence, the subjective bias and random error introduced by manual operation are eliminated, making the test process standardized and the results quantifiable, thereby improving the efficiency and objectivity of the evaluation.

[0006] This specification provides a method for testing the accuracy of matching an inflatable lung 3D model with the actual lung structure, including: Acquire the test operation sequence and the 3D model of the inflatable lung and its corresponding intraoperative laparoscopic video; wherein, the surface of the 3D model of the inflatable lung is marked with several simulated marker points, and the actual lung structure in the intraoperative laparoscopic video is marked with real marker points corresponding to the simulated marker points; The detection system automatically registers the inflated lung 3D model with the actual lung structure based on the test operation sequence to obtain a registration result; wherein, the registration result includes the coordinates of the projection points of the simulated marker points in the endoscopic video coordinate system; The positional deviation between the coordinates of the projected point and the corresponding coordinates of the real marker point is determined based on the registration result. The model matching accuracy of the system under test is evaluated based on the positional deviation.

[0007] Optionally, the simulated marker points include at least two of the following types: Location of lesions, including the location of lung nodules; Feature points, including pixel values ​​that are different from those of points in the adjacent region; Regular points, including boundary points.

[0008] Optionally, obtaining the test operation sequence includes: An initial operation sequence set is generated based on the element information of each interactive element in the human-computer interaction interface of the system to be tested; wherein, the element information includes the position information of the element and the executable action information; Based on the acquired test requirements, target element information is sequentially filtered from the initial operation sequence set to generate the test operation sequence.

[0009] Optionally, the target element information includes the number of actions performed on the target interactive element and / or the waiting time after performing the actions.

[0010] Optional, also includes: The registration result includes the mapped model obtained by registering and mapping the 3D model of the inflatable lung to the endoscopic video coordinate system; Calculate the morphological deviation between the surface of the mapping model and the actual lung structure surface in the endoscopic video; The model matching accuracy of the system under test is evaluated based on the positional deviation and the morphological deviation.

[0011] Optional, also includes: Using the same test operation sequence, inflatable lung 3D model and endoscopic video, the system under test was tested multiple times to obtain multiple test results; Analyze the statistical distribution differences of the positional deviations in multiple test results to evaluate the consistency of the registration results of the system under test.

[0012] Optional, also includes: Multiple sets of different test data were obtained, each set of test data including a 3D model of an inflatable lung and a corresponding endoscopic video. Based on the same test operation sequence, the system under test is tested using each set of test data to obtain multiple test results; Based on the distribution of positional deviations in all test results, the matching robustness of the system under test under different physiological structures is evaluated.

[0013] This specification provides a device for testing the accuracy of matching an inflatable lung 3D model with the actual lung structure, including: The acquisition module is used to acquire the test operation sequence and the 3D model of the inflatable lung and its corresponding intraoperative laparoscopic video; wherein, the surface of the 3D model of the inflatable lung is marked with several simulated marker points, and the actual lung structure in the intraoperative laparoscopic video is marked with real marker points corresponding to the simulated marker points; The registration module is used by the system under test to automatically register the 3D model of the inflated lung with the actual lung structure based on the test operation sequence, and obtain the registration result; wherein, the registration result includes the coordinates of the projection points of the simulated marker points in the endoscopic video coordinate system; The determination module is used to determine the positional deviation between the coordinates of the projected point and the corresponding coordinates of the real marker point based on the registration result; An evaluation module is used to evaluate the model matching accuracy of the system under test based on the positional deviation.

[0014] Optionally, the simulated marker points include at least two of the following types: Location of lesions, including the location of lung nodules; Feature points, including pixel values ​​that are different from those of points in the adjacent region; Regular points, including boundary points.

[0015] Optionally, obtaining the test operation sequence includes: An initial operation sequence set is generated based on the element information of each interactive element in the human-computer interaction interface of the system to be tested; wherein, the element information includes the position information of the element and the executable action information; Based on the acquired test requirements, target element information is sequentially filtered from the initial operation sequence set to generate the test operation sequence.

[0016] Optionally, the target element information includes the number of actions performed on the target interactive element and / or the waiting time after performing the actions.

[0017] Optional, also includes: The registration result includes the mapped model obtained by registering and mapping the 3D model of the inflatable lung to the endoscopic video coordinate system; Calculate the morphological deviation between the surface of the mapping model and the actual lung structure surface in the endoscopic video; The model matching accuracy of the system under test is evaluated based on the positional deviation and the morphological deviation.

[0018] Optional, also includes: Using the same test operation sequence, inflatable lung 3D model and endoscopic video, the system under test was tested multiple times to obtain multiple test results; Analyze the statistical distribution differences of the positional deviations in multiple test results to evaluate the consistency of the registration results of the system under test.

[0019] Optional, also includes: Multiple sets of different test data were obtained, each set of test data including a 3D model of an inflatable lung and a corresponding endoscopic video. Based on the same test operation sequence, the system under test is tested using each set of test data to obtain multiple test results; Based on the distribution of positional deviations in all test results, the matching robustness of the system under test under different physiological structures is evaluated.

[0020] This specification also provides an electronic device, wherein the electronic device includes: A processor; and a memory storing computer-executable instructions, which, when executed, cause the processor to perform any of the methods described above.

[0021] This specification also provides a computer-readable storage medium that stores one or more programs that, when executed by a processor, implement any of the methods described above.

[0022] In this invention, a predefined test operation sequence controls the system under test to automatically complete the entire registration process, eliminating subjective bias and random errors introduced by manual operation. This standardizes the testing process, quantifies the results, and improves the efficiency and objectivity of the evaluation. By setting various types of simulated marker points, including lesion points, feature points, and routine points, the registration performance of the navigation system in different physiological structural regions can be comprehensively evaluated, especially ensuring the effectiveness of testing the core function of lesion localization. Evaluation is not only based on the projection position deviation of the marker points, but also innovatively incorporates the calculation of model surface morphology deviation. This allows for cross-validation and comprehensive evaluation of the registration results from both point and surface spatial dimensions, making the evaluation of the system's matching accuracy more comprehensive and reliable. Through the design of consistency and robustness tests, the stability of the navigation system's results under different operating cycles and its adaptability to different patient physiological structures can be thoroughly evaluated. This provides crucial data support for evaluating the clinical usability and reliability of the system, going beyond the scope of single-precision testing. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 A schematic diagram illustrating the principle of a method for testing the accuracy of matching an inflatable lung 3D model with the actual lung structure, provided in an embodiment of this specification. Figure 2 A schematic diagram of a device for testing the accuracy of matching an inflatable lung 3D model with the actual lung structure, provided in an embodiment of this specification. Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this specification; Figure 4 This is a schematic diagram of a computer-readable medium provided for embodiments of this specification. Detailed Implementation

[0025] The following description is intended to disclose the present invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art. The basic principles of the invention defined in the following description can be applied to other embodiments, modifications, improvements, equivalents, and other technical solutions that do not depart from the spirit and scope of the invention.

[0026] The following is in conjunction with the appendix Figure 1-4 Exemplary embodiments of the invention will be described more fully here. However, exemplary embodiments can be implemented in many forms and should not be construed as limiting the invention to the embodiments set forth herein. Rather, these exemplary embodiments are provided to make the invention more comprehensive and complete, and to facilitate a full communication of the inventive concept to those skilled in the art. The same reference numerals in the figures denote the same or similar elements, components, or parts, and therefore repeated descriptions of them are omitted.

[0027] Subject to the technical concept of this invention, the features, structures, characteristics or other details described in a particular embodiment may be combined in one or more other embodiments in a suitable manner.

[0028] In the description of specific embodiments, the features, structures, characteristics, or other details described in this invention are intended to enable those skilled in the art to fully understand the embodiments. However, it is not excluded that those skilled in the art can practice the technical solutions of this invention without one or more of the specific features, structures, characteristics, or other details.

[0029] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0030] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0031] The terms “and / or” or “and / or” include all combinations of any one or more of the listed items.

[0032] Figure 1 This is a schematic diagram illustrating the principle of a method for testing the accuracy of matching an inflatable lung 3D model with the actual lung structure, as provided in an embodiment of this specification. The method may include: S110: Obtain the test operation sequence and the 3D model of the inflatable lung and its corresponding intraoperative laparoscopic video; wherein, the surface of the 3D model of the inflatable lung is marked with several simulated marker points, and the actual lung structure in the intraoperative laparoscopic video is marked with real marker points corresponding to the simulated marker points; Optionally, the simulated marker points include at least two of the following types: Location of lesions, including the location of lung nodules; Feature points, including pixel values ​​that are different from those of points in the adjacent region; Regular points, including boundary points.

[0033] In the specific implementation of this specification, to ensure the comprehensiveness of the test, the selected marker points should cover multiple types. These include, but are not limited to: lesion location points, which are directly marked at the center or edge of lesions such as lung nodules, used to test the system's ability to locate core targets; feature points, which are located at vascular intersections, bifurcations, or points with textures significantly different from the surrounding areas, utilizing the differences in their pixel values ​​or texture features; and routine points, which are distributed in non-featured ordinary areas on the surface of lung lobes or on the boundaries of interlobar fissures, lung edges, etc., used to evaluate the system's general registration performance in non-featured areas. By integrating these points of different natures, a comprehensive test list is formed.

[0034] Optionally, obtaining the test operation sequence includes: An initial operation sequence set is generated based on the element information of each interactive element in the human-computer interaction interface of the system to be tested; wherein, the element information includes the position information of the element and the executable action information; Based on the acquired test requirements, target element information is sequentially filtered from the initial operation sequence set to generate the test operation sequence.

[0035] In the specific implementation of this specification, firstly, automated testing tools are used to parse the human-computer interaction interface of the navigation system under test, identify and record all interactive UI elements (such as buttons, sliders, menu items, etc.) and their attributes, including their position coordinates on the screen and the actions they can perform (such as clicking, dragging, inputting, etc.), thereby forming a complete initial operation sequence set. Subsequently, according to the specific test case requirements (e.g., "execute the entire process from model import to registration completion"), the required target elements and their action information are selected from this initial set according to the correct logical operation order, and this information is combined into a test operation sequence that can be executed by the automated testing engine.

[0036] Optionally, the target element information includes the number of actions performed on the target interactive element and / or the waiting time after performing the actions.

[0037] In the specific implementation of this specification, to enhance the reliability of the test sequence and simulate real-world operating scenarios, more detailed parameters need to be configured for the target element information in addition to basic actions. For example, for a button that needs to be clicked, the number of consecutive clicks can be specified; or, after completing a time-consuming operation (such as model loading), a waiting time parameter needs to be inserted into the sequence to pause the execution of the test script for a period of time, ensuring that the system under test has enough time to complete its internal processing and prepare to receive the next instruction, thereby avoiding test failures due to system response delays.

[0038] S120: The system under test automatically registers the 3D model of the inflated lung with the actual lung structure based on the test operation sequence to obtain a registration result; wherein, the registration result includes the coordinates of the projection points of the simulated marker points in the endoscopic video coordinate system; S130: Determine the positional deviation between the coordinates of the projected point and the corresponding coordinates of the real marker point based on the registration result; S140: Evaluate the model matching accuracy of the system under test based on the positional deviation.

[0039] Optional, also includes: The registration result includes the mapped model obtained by registering and mapping the 3D model of the inflatable lung to the endoscopic video coordinate system; Calculate the morphological deviation between the surface of the mapping model and the actual lung structure surface in the endoscopic video; The model matching accuracy of the system under test is evaluated based on the positional deviation and the morphological deviation.

[0040] In the specific implementation of this specification, the registration results obtained from the system under test should also include the mapped model after converting the entire inflatable lung 3D model to the endoscopic video coordinate system. Using a 3D distance calculation algorithm, the spatial distance between the surface of this mapped model and the surface of the real lung structure extracted from the endoscopic video is compared to calculate a deviation value reflecting the overall morphological fit. The final model matching accuracy evaluation report should be derived by comprehensively considering both the positional deviation of the discrete points and the morphological deviation of the continuous surfaces.

[0041] Optional, also includes: Using the same test operation sequence, inflatable lung 3D model and endoscopic video, the system under test was tested multiple times to obtain multiple test results; Analyze the statistical distribution differences of the positional deviations in multiple test results to evaluate the consistency of the registration results of the system under test.

[0042] In the specific implementation of this specification, consistency testing requires repeated testing of the same system under test in identical testing environments (i.e., using the same test operation sequence, the same set of inflatable lung models, and endoscopic videos). All positional deviation data obtained from each test are collected, and the statistical characteristics of these datasets are analyzed, such as calculating the average, variance, or confidence interval of the results from multiple tests. By observing the fluctuation range and distribution of these deviation values, the repeatability and stability of the navigation system's registration output, i.e., the system's consistency performance, is determined.

[0043] Optional, also includes: Multiple sets of different test data were obtained, each set of test data including a 3D model of an inflatable lung and a corresponding endoscopic video. Based on the same test operation sequence, the system under test is tested using each set of test data to obtain multiple test results; Based on the distribution of positional deviations in all test results, the matching robustness of the system under test under different physiological structures is evaluated.

[0044] In the specific implementation of this specification, robustness testing requires preparing a database containing multiple sets of test data, each from different cases, including their unique inflated lung models and endoscopic videos. Using the same carefully designed test sequence, the system to be tested is tested sequentially with each set of data. All positional deviation results generated after all test runs are collected and comprehensively analyzed (e.g., comparing the mean distribution and dispersion of deviations between different case groups). The system's generalization ability and robustness are evaluated by observing changes in performance when facing different patients and different physiological structures; that is, whether the system can maintain reliable registration accuracy under various conditions.

[0045] In this invention, a predefined test operation sequence controls the system under test to automatically complete the entire registration process, eliminating subjective bias and random errors introduced by manual operation. This standardizes the testing process, quantifies the results, and improves the efficiency and objectivity of the evaluation. By setting various types of simulated marker points, including lesion points, feature points, and routine points, the registration performance of the navigation system in different physiological structural regions can be comprehensively evaluated, especially ensuring the effectiveness of testing the core function of lesion localization. Evaluation is not only based on the projection position deviation of the marker points, but also innovatively incorporates the calculation of model surface morphology deviation. This allows for cross-validation and comprehensive evaluation of the registration results from both point and surface spatial dimensions, making the evaluation of the system's matching accuracy more comprehensive and reliable. Through the design of consistency and robustness tests, the stability of the navigation system's results under different operating cycles and its adaptability to different patient physiological structures can be thoroughly evaluated. This provides crucial data support for evaluating the clinical usability and reliability of the system, going beyond the scope of single-precision testing.

[0046] Figure 2 This is a schematic diagram illustrating the principle of a device for testing the accuracy of matching an inflatable lung 3D model with the actual lung structure, as provided in an embodiment of this specification. The device may include: The acquisition module 10 is used to acquire the test operation sequence and the 3D model of the inflatable lung and its corresponding intraoperative laparoscopic video; wherein, the surface of the 3D model of the inflatable lung is marked with a number of simulated marker points, and the actual lung structure in the intraoperative laparoscopic video is marked with real marker points corresponding to the simulated marker points; The registration module 20 is used by the system under test to automatically register the 3D model of the inflated lung with the actual lung structure based on the test operation sequence, and obtain the registration result; wherein, the registration result includes the coordinates of the projection points of the simulated marker points in the endoscopic video coordinate system; The determination module 30 is used to determine the positional deviation between the coordinates of the projected point and the corresponding coordinates of the real marker point based on the registration result; Evaluation module 40 is used to evaluate the model matching accuracy of the system under test based on the positional deviation.

[0047] Optionally, the simulated marker points include at least two of the following types: Location of lesions, including the location of lung nodules; Feature points, including pixel values ​​that are different from those of points in the adjacent region; Regular points, including boundary points.

[0048] Optionally, obtaining the test operation sequence includes: An initial operation sequence set is generated based on the element information of each interactive element in the human-computer interaction interface of the system to be tested; wherein, the element information includes the position information of the element and the executable action information; Based on the acquired test requirements, target element information is sequentially filtered from the initial operation sequence set to generate the test operation sequence.

[0049] Optionally, the target element information includes the number of actions performed on the target interactive element and / or the waiting time after performing the actions.

[0050] Optional, also includes: The registration result includes the mapped model obtained by registering and mapping the 3D model of the inflatable lung to the endoscopic video coordinate system; Calculate the morphological deviation between the surface of the mapping model and the actual lung structure surface in the endoscopic video; The model matching accuracy of the system under test is evaluated based on the positional deviation and the morphological deviation.

[0051] Optional, also includes: Using the same test operation sequence, inflatable lung 3D model and endoscopic video, the system under test was tested multiple times to obtain multiple test results; Analyze the statistical distribution differences of the positional deviations in multiple test results to evaluate the consistency of the registration results of the system under test.

[0052] Optional, also includes: Multiple sets of different test data were obtained, each set of test data including a 3D model of an inflatable lung and a corresponding endoscopic video. Based on the same test operation sequence, the system under test is tested using each set of test data to obtain multiple test results; Based on the distribution of positional deviations in all test results, the matching robustness of the system under test under different physiological structures is evaluated.

[0053] The functions of the apparatus in this embodiment have been described in the above method embodiments. Therefore, for any parts not detailed in this embodiment, please refer to the relevant descriptions in the foregoing embodiments, which will not be repeated here.

[0054] Based on the same inventive concept, embodiments of this specification also provide an electronic device.

[0055] The following describes embodiments of the electronic device of the present invention, which can be considered as specific implementations of the methods and apparatus embodiments of the present invention described above. Details described in the embodiments of the electronic device of the present invention should be considered as supplements to the methods or apparatus embodiments described above; details not disclosed in the embodiments of the electronic device of the present invention can be implemented with reference to the methods or apparatus embodiments described above.

[0056] Figure 3 This is a schematic diagram of an electronic device provided as an embodiment of this specification. Refer to the following... Figure 3 The electronic device 300 according to this embodiment of the present invention will be described. Figure 3 The electronic device 300 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0057] like Figure 3 As shown, the electronic device 300 is presented in the form of a general-purpose computing device. The components of the electronic device 300 may include, but are not limited to: at least one processing unit 310, at least one storage unit 320, a bus 330 connecting different system components (including storage unit 320 and processing unit 310), a display unit 340, etc.

[0058] The storage unit stores program code that can be executed by the processing unit 310, causing the processing unit 310 to perform the steps described in the processing method section of this specification according to various exemplary embodiments of the present invention. For example, the processing unit 310 can perform, for example... Figure 1 The steps are shown.

[0059] The storage unit 320 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 3201 and / or a cache storage unit 3202, and may further include a read-only memory unit (ROM) 3203.

[0060] The storage unit 320 may also include a program / utility 3204 having a set (at least one) program module 3205, such program module 3205 including but not limited to: an operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0061] Bus 330 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0062] Electronic device 300 can also communicate with one or more external devices 400 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable viewers to interact with electronic device 300, and / or with any device that enables electronic device 300 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 350. Furthermore, electronic device 300 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 360. Network adapter 360 can communicate with other modules of electronic device 300 via bus 330. It should be understood that, although... Figure 3 As not shown, other hardware and / or software modules may be used in conjunction with electronic device 300, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0063] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described in this invention can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this invention can be embodied in the form of a software product, which can be stored in a computer-readable storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, or network device, etc.) to execute the method described above according to this invention. When the computer program is executed by a data processing device, it enables the computer-readable medium to implement the method described above, i.e.: as... Figure 1 The method shown.

[0064] Figure 4 This is a schematic diagram of a computer-readable medium provided for embodiments of this specification.

[0065] accomplish Figure 1 The computer program of the method shown can be stored on one or more computer-readable media. A computer-readable medium can be a readable signal medium or a readable storage medium. A readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0066] The computer-readable storage medium may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The readable storage medium may also be any readable medium other than a readable storage medium, capable of transmitting, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0067] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the audience's computing device, partially on the audience's device, as a standalone software package, partially on the audience's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the audience's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0068] In summary, the present invention can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that in practice, general-purpose data processing devices such as microprocessors or digital signal processors (DSPs) can be used to implement some or all of the functions of some or all of the components according to the embodiments of the present invention. The present invention can also be implemented as a device or apparatus program (e.g., a computer program and computer program product) for performing part or all of the methods described herein. Such programs implementing the present invention can be stored on a computer-readable medium or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0069] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the present invention is not inherently related to any specific computer, virtual device, or electronic device, and various general-purpose devices can also implement the present invention. The above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0070] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0071] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for testing the accuracy of matching an inflatable lung 3D model with the actual lung structure, characterized in that, include: Acquire the test operation sequence and the 3D model of the inflatable lung and its corresponding intraoperative laparoscopic video; wherein, the surface of the 3D model of the inflatable lung is marked with several simulated marker points, and the actual lung structure in the intraoperative laparoscopic video is marked with real marker points corresponding to the simulated marker points; The detection system automatically registers the inflated lung 3D model with the actual lung structure based on the test operation sequence to obtain a registration result; wherein, the registration result includes the coordinates of the projection points of the simulated marker points in the endoscopic video coordinate system; The positional deviation between the coordinates of the projected point and the corresponding coordinates of the real marker point is determined based on the registration result. The model matching accuracy of the system under test is evaluated based on the positional deviation.

2. The method for testing the accuracy of matching the 3D model of an inflatable lung with the actual lung structure as described in claim 1, characterized in that, The simulated markers include at least two of the following types: Location of lesions, including the location of lung nodules; Feature points, including pixel values ​​that are different from those of points in the adjacent region; Regular points, including boundary points.

3. The method for testing the accuracy of matching the 3D model of the inflatable lung with the actual lung structure as described in claim 2, characterized in that, The acquisition of the test operation sequence includes: An initial operation sequence set is generated based on the element information of each interactive element in the human-computer interaction interface of the system to be tested; wherein, the element information includes the position information of the element and the executable action information; Based on the acquired test requirements, target element information is sequentially filtered from the initial operation sequence set to generate the test operation sequence.

4. The method for testing the accuracy of matching the 3D model of the inflatable lung with the actual lung structure as described in claim 3, characterized in that, The target element information includes the number of actions performed on the target interactive element and / or the waiting time after performing the actions.

5. The method for testing the accuracy of matching the 3D model of the inflatable lung with the actual lung structure as described in claim 4, characterized in that, Also includes: The registration result includes the mapped model obtained by registering and mapping the 3D model of the inflatable lung to the endoscopic video coordinate system; Calculate the morphological deviation between the surface of the mapping model and the actual lung structure surface in the endoscopic video; The model matching accuracy of the system under test is evaluated based on the positional deviation and the morphological deviation.

6. The method for testing the accuracy of matching the 3D model of an inflatable lung with the actual lung structure as described in claim 5, characterized in that, Also includes: Using the same test operation sequence, inflatable lung 3D model and endoscopic video, the system under test was tested multiple times to obtain multiple test results; Analyze the statistical distribution differences of the positional deviations in multiple test results to assess the consistency of the registration results of the system under test.

7. The method for testing the accuracy of matching the 3D model of an inflatable lung with the actual lung structure as described in claim 6, characterized in that, Also includes: Multiple sets of different test data were obtained, each set of test data including a 3D model of an inflatable lung and a corresponding endoscopic video. Based on the same test operation sequence, the system under test is tested using each set of test data to obtain multiple test results; Based on the distribution of positional deviations in all test results, the matching robustness of the system under test under different physiological structures is evaluated.

8. A device for testing the accuracy of matching an inflatable lung 3D model with the actual lung structure, characterized in that, include: The acquisition module is used to acquire the test operation sequence and the 3D model of the inflatable lung and its corresponding intraoperative laparoscopic video; wherein, the surface of the 3D model of the inflatable lung is marked with several simulated marker points, and the actual lung structure in the intraoperative laparoscopic video is marked with real marker points corresponding to the simulated marker points; The registration module is used by the system under test to automatically register the 3D model of the inflated lung with the actual lung structure based on the test operation sequence, and obtain the registration result; wherein, the registration result includes the coordinates of the projection points of the simulated marker points in the endoscopic video coordinate system; The determination module is used to determine the positional deviation between the coordinates of the projected point and the corresponding coordinates of the real marker point based on the registration result; An evaluation module is used to evaluate the model matching accuracy of the system under test based on the positional deviation.

9. An electronic device, wherein, The electronic device includes: A processor; and a memory storing computer-executable instructions, which, when executed, cause the processor to perform the method according to any one of claims 1-7.

10. A computer-readable storage medium, wherein, The computer-readable storage medium stores one or more programs that, when executed by a processor, implement the method of any one of claims 1-7.

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