Simulation system for ovum taking operation training

Abstract

The embodiment of the invention discloses a simulation system for ovum taking operation training. The simulation system comprises a real-time ultrasonic picture rendering module, a force feedback interaction hardware module and a system function integration module. A specific embodiment of the method comprises the following steps: a real-time ultrasonic image rendering module is configured to determine a propagation path and interaction of ultrasonic waves to obtain a propagation fragment set corresponding to the ultrasonic waves; performing random texture sampling on each propagation fragment to obtain an intensity distribution value; executing an image processing task corresponding to the imaging picture to obtain a real-time ultrasonic rendering picture; the force feedback interaction hardware module is configured to perform force feedback processing; and the system function integration module is configured to render the real-time ultrasonic picture and obtain force feedback data so as to adjust the real-time ultrasonic rendering picture. According to the implementation mode, key operation steps and technical key points in the ovum taking operation can be accurately and efficiently restored, clinical doctors are effectively helped to rapidly master operation skills, and better treatment experience is provided for patients.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the field of medical technology, and in particular to a simulation system for egg retrieval surgery training. Background Art

[0002] In the field of assisted reproductive technology, egg retrieval, a critical procedure, has garnered significant attention. This procedure requires extremely high precision, and improper performance can easily lead to numerous complications. Currently, in clinical practice, this delicate procedure relies primarily on the accumulated experience of senior physicians. Research has shown that the use of simulation training systems can effectively improve proficiency, but novice physicians generally face a lack of clinical practice opportunities and effective training methods. Currently, only one training device, the PICKUPSIM, remains on the market, but clinical feedback indicates that its fidelity fails to meet stringent teaching requirements. Furthermore, the device utilizes clinical image display technology, resulting in limited image changes when the handle is moved, severely hindering the improvement of procedural skills. This technical limitation continues to dictate the continued reliance on senior physicians in clinical practice, creating a vicious cycle of experience reliance, insufficient training, and increasing risk, becoming a bottleneck restricting the development of reproductive medicine professionals.

[0003] With the continuous advancement of real-time ultrasound simulation imaging technology, it has become possible to use ultrasound rendering during the operation process. Combined with the corresponding hardware equipment, it can achieve a more realistic and immersive operation simulation.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the inventive concept and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art. Summary of the Invention

[0005] The content of this disclosure is used to briefly introduce concepts that will be described in detail in the detailed description section below. The content of this disclosure is not intended to identify key features or essential features of the claimed technical solution, nor is it intended to limit the scope of the claimed technical solution.

[0006] Some embodiments of the present disclosure provide a simulation system for egg retrieval surgery training to solve one or more of the technical problems mentioned in the above background technology section.

[0007] In a first aspect, some embodiments of the present disclosure provide a simulation system for egg retrieval surgery training, including: a real-time ultrasound image rendering module, a force feedback interaction hardware module, and a system function integration module, wherein: the real-time ultrasound image rendering module is configured to: determine the propagation path and interaction of ultrasound through the organ simulation model at the current time through the sound wave propagation path tracking technology, and obtain a propagation segment set corresponding to the ultrasound; perform random texture sampling on each propagation segment in the propagation segment set to obtain the intensity distribution value of the ultrasound corresponding to the microscopic tissue particles in the imaging plane corresponding to the propagation segment set; based on the intensity distribution value, perform image processing tasks corresponding to the imaging picture. The force feedback interaction hardware module is configured to: utilize the force feedback device and the force feedback framework to perform force feedback processing according to the probe data during the execution of the simulated egg retrieval surgery, wherein the force feedback device and the force feedback framework are set based on the corresponding operating characteristics of the simulated egg retrieval surgery; the system function integration module is configured to: render the real-time ultrasound image through the rendering thread, and obtain the force feedback data output by the force feedback interaction hardware module through the logic thread, so as to adjust the real-time ultrasound rendering image of the simulated egg retrieval surgery at the current time according to the force feedback data.

[0008] In a second aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by one or more processors, the one or more processors implement the method described in any implementation manner in the first aspect.

[0009] In a third aspect, some embodiments of the present disclosure provide a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the method described in any implementation manner in the first aspect is implemented.

[0010] The various embodiments disclosed above have the following beneficial effects: Through the simulation system for egg retrieval surgery training of some embodiments of the present disclosure, the key operating steps and technical points of the egg retrieval surgery can be accurately and efficiently reproduced, effectively helping clinicians quickly master surgical techniques and providing patients with a better treatment experience. Based on this, the simulation system for egg retrieval surgery training of some embodiments of the present disclosure includes: a real-time ultrasound image rendering module, a force feedback interaction hardware module, and a system function integration module. The real-time ultrasound image rendering module is configured to: determine the propagation path and interaction of the ultrasound wave through the organ simulation model at the current time using sound wave propagation path tracing technology to obtain a set of propagation segments corresponding to the ultrasound wave; perform random texture sampling on each propagation segment in the propagation segment set to obtain the intensity distribution value corresponding to the microscopic tissue particles in the imaging plane corresponding to the propagation segment set; and perform image processing tasks corresponding to the imaging image based on the intensity distribution value to obtain a real-time ultrasound rendering image of the simulated egg retrieval surgery at the current time. Here, the real-time ultrasound image rendering module can simulate the propagation segment set in the organ simulation model using ultrasound technology. Random texture sampling is used to enhance the image intensity of microscopic tissue particles on the imaging plane, making the image plane more realistic and more closely resembling a realistic egg retrieval model. Furthermore, through image processing tasks, a real-time ultrasound rendering of the egg retrieval surgery at the current time is generated under ultrasound propagation, which is then presented to the clinician. The force feedback interaction hardware module is then configured to perform force feedback processing based on probe data from the simulated egg retrieval surgery using a force feedback device and a force feedback framework. The force feedback device and force feedback framework are configured based on the operational characteristics of the simulated egg retrieval surgery. The force feedback interaction hardware module effectively assists clinicians in precisely manipulating the probe during the simulated egg retrieval surgery, informing them through force how to correctly operate the probe, thereby achieving efficient egg retrieval during the procedure. Finally, the system function integration module is configured to render the real-time ultrasound image via a rendering thread, obtain force feedback data output by the force feedback interaction hardware module via a logic thread, and adjust the real-time ultrasound rendering of the simulated egg retrieval surgery at the current time based on this force feedback data. Here, through the system function integration module, precise control of the force feedback interaction hardware module and the real-time ultrasound image rendering module can be achieved, effective interaction between the two modules can be realized, and the normal execution of the simulated egg retrieval operation can be ensured. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The above and other features, advantages, and aspects of the various embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0012] Figure 1 is a flow chart of some embodiments of a simulation system for egg retrieval surgery training according to the present disclosure;

[0013] Figure 2 is a schematic structural diagram of an electronic device suitable for implementing some embodiments of the present disclosure;

[0014] Figure 3 is a schematic diagram of a model scene in a simulation system for egg retrieval surgery training according to the present disclosure;

[0015] Figure 4 is a schematic diagram of an ultrasound-simulated egg retrieval process in a simulation system for egg retrieval surgery training according to the present disclosure;

[0016] Figure 5 is a schematic diagram of the hardware configuration in a simulation system for egg retrieval surgery training according to the present disclosure;

[0017] Figure 6 is a schematic diagram of uterus, bladder and follicle aspiration in a simulation system for oocyte retrieval surgery training according to the present disclosure;

[0018] Figure 7 Schematic diagram of operation prompts and warnings in a simulation system for egg retrieval surgery training according to the present disclosure. DETAILED DESCRIPTION

[0019] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of protection of the present disclosure.

[0020] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure may be combined with each other.

[0021] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0022] It should be noted that the modifications of "one" and "multiple" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, they should be understood as "one or more".

[0023] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0024] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0025] refer to Figure 1 , shows a simulation system 100 for egg retrieval surgery training according to the present disclosure, including: a real-time ultrasound image rendering module, a force feedback interaction hardware module, and a system function integration module. The real-time ultrasound image rendering module generates an execution image at a certain moment in the simulated egg retrieval surgery process under the interaction of ultrasound in real time. The force feedback interaction hardware module can be an interactive hardware module that provides force feedback for the operation behavior of the ultrasound probe through force feedback and a force feedback framework. The ultrasound probe can be the probe used in the egg retrieval surgery. The system function integration module can be a module that integrates various system functions in the simulated egg retrieval surgery process and coordinates the various modules.

[0026] In some embodiments, the above-mentioned real-time ultrasound image rendering module is configured to: determine the propagation path and interaction of the ultrasound wave through the organ simulation model at the current time through the sound wave propagation path tracking technology, and obtain the propagation segment set corresponding to the ultrasound wave. Among them, the propagation path is the physical path of the ultrasound wave from the transmitting probe to the target tissue (or reflected back to the receiving probe), which is affected by the acoustic properties of the medium (such as density, sound speed, attenuation coefficient) and the organ structure. Interaction is the energy interaction behavior between the sound wave and the tissue. Interaction includes: reflection, refraction, scattering and attenuation. Reflection is the return of energy caused by the difference in acoustic impedance on both sides of the interface (such as organ boundaries, lesion areas). Refraction is the change in the direction of the sound wave due to the change in the sound speed of the medium (such as the junction of bone and soft tissue). Scattering is the diffusion of sound waves in multiple directions due to tiny structures (such as cells, fibers). Attenuation is the weakening of sound wave energy as the propagation distance increases (due to absorption and scattering).

[0027] Acoustic wave propagation path tracing technology is used to determine the path and characteristics of acoustic waves propagating in a medium (i.e., an organ simulation model). The organ simulation model can be the simulated egg retrieval model. The propagation segment corresponding to the ultrasonic wave refers to the sound field distribution and its propagation state formed in a certain time period or spatial range when the ultrasonic wave propagates in the medium. Due to the high frequency and short wavelength characteristics of ultrasonic waves, their propagation segments usually show clear wavefront, reflection, refraction, attenuation and other characteristics. The physical composition of the propagation segment: (1) Time dimension: The propagation segment of the ultrasonic wave can be understood as the dynamic propagation process of the acoustic wave in the medium within the time window from emission to reception. For example, the propagation segment of the pulsed ultrasonic wave includes the entire process of transmitting the pulse, propagation path, target reflection or scattering, and echo reception. (2) Spatial dimension: At a fixed moment, the propagation segment of the ultrasonic wave corresponds to the spatial distribution of the acoustic wave in the medium (such as wavefront shape, energy density distribution, etc.). For example, the propagation form of plane waves, spherical waves or cylindrical waves at the interface of different media. Here, the traditional ultrasonic simulation method relies on solving the wave equation of the acoustic wave. However, due to the relatively complex calculations involved, it is difficult to achieve real-time rendering. In simulations, strictly physically correct ultrasound images are not required, but a higher rendering frame rate is needed to ensure a smoother operation. A smoother operation process can significantly improve the training experience, enabling trainees to quickly respond to visual cues provided by the ultrasound image and make timely adjustments during the operation. Ray tracing is a commonly used rendering technique. At the scale of organs, the wave nature of ultrasound waves can be neglected and approximated as rays. Propagation follows Fresnel's laws. Using acoustic wave propagation path tracing, the path and interaction of ultrasound waves as they pass through the model can be quickly calculated. When ultrasound waves propagate through biological tissue, three main phenomena occur at tissue interfaces: attenuation, refraction, and reflection. Attenuation primarily affects the intensity of ultrasound waves, manifesting as a decrease in grayscale in the ultrasound image. Refraction and reflection follow Snell's law and Fresnel's equations. When ultrasound waves enter tissue, they theoretically generate numerous new refracted and reflected waves. Each new wave may create an additional propagation path, requiring additional tracing.

[0028] In some embodiments, the real-time ultrasound image rendering module is configured to perform random texture sampling on each propagation segment in the propagation segment set to obtain intensity distribution values of ultrasound waves corresponding to microscopic tissue particles in the imaging plane corresponding to the propagation segment set.

[0029] Here, random texture sampling can effectively simulate the microscopic tissue particles present in organ tissues. These tissue particles can scatter ultrasound waves, resulting in a texture with a noisy texture. The intensity distribution value can be the texture intensity value of each microscopic tissue particle in the imaging plane. That is, different intensity values represent different textures of microscopic tissue particles. The texture intensity value of an organ is a key parameter in medical image analysis, used to quantitatively describe the texture characteristics and intensity distribution of organ tissue in an image. This feature extraction and analysis is of great significance in disease diagnosis, pathological assessment, and therapeutic efficacy monitoring. The texture intensity value can refer to the intensity characteristics of local grayscale or color changes exhibited by organ tissue in medical images (such as ultrasound, CT, and MRI). It reflects the complexity, uniformity, and directionality of tissue structure, for example, the texture differences between normal tissue and diseased areas (such as tumors and fibrosis). The intensity distribution value can be the distribution of texture intensity values of each microscopic tissue particle in the imaging plane.

[0030] As an example, at least one texture adjustment region for texture adjustment can be randomly sampled from the imaging plane corresponding to each propagation segment. Then, a convolutional neural network (CNN) is used to automatically learn texture features, such as using a U-Net to segment lesion regions and a ResNet to classify texture patterns, to automatically determine the texture intensity value corresponding to the at least one texture adjustment region. The obtained original texture intensity distribution and at least one texture intensity value corresponding to the imaging plane are then determined as the intensity distribution value.

[0031] In some embodiments, the real-time ultrasound image rendering module is configured to perform an image processing task corresponding to the imaging image based on the intensity distribution value, thereby obtaining a real-time ultrasound rendering image of the simulated egg retrieval surgery at the current time. The image processing task may be a task that performs various image processing operations on the imaging image. For example, the image processing task may be an image enhancement task. The imaging image may be a display image corresponding to the imaging plane within the propagation segment set.

[0032] As an example, first determine the microscopic tissue particle distribution corresponding to the intensity distribution value. Each texture intensity value in the intensity distribution value corresponds to a corresponding microscopic tissue particle distribution. The distribution of each texture intensity value corresponding to the intensity distribution value represents the tissue particle distribution of each microscopic tissue particle on the imaging plane. Then, each microscopic tissue particle distribution is added to the imaging plane to produce a real-time ultrasound rendering image.

[0033] In some optional implementations of some embodiments, the real-time ultrasound image rendering module may determine the propagation path and interaction of the ultrasound wave through the organ simulation model at the current time using sound wave propagation path tracing technology, and obtain a set of propagation segments corresponding to the ultrasound wave, including the following steps:

[0034] The first step is to use the sound wave propagation path tracing technology to determine the propagation path and interaction of ultrasound waves through the organ simulation model at the current time, and obtain a set of propagation rays. Propagation rays can be simplified sound wave propagation trajectories, which are used to intuitively describe the sound field distribution and key interaction nodes (such as reflection points and focal areas). Propagation rays refer to geometric representations used to simplify the description of sound wave or light wave propagation paths in the field of acoustics or optics. Complex wave phenomena (such as reflection, refraction, and scattering) are abstracted into straight or curved paths to help analyze the direction of energy transfer and key interaction nodes (such as reflection points and focal areas).

[0035] In the second step, importance sampling is performed on each propagation ray in the propagation ray set to obtain an important propagation ray set, wherein the important propagation ray may be a propagation ray with important propagation characteristics.

[0036] For example, to avoid exponential growth in the number of rays (which would otherwise result in excessive computational time), importance sampling is employed. This technique requires generating only one new ray at a time. However, if this is the only approach, the number of rays generated may be too sparse, resulting in loss of valid information. To alleviate this issue, the system uses a Monte Carlo method for multiple sampling. In each sampling iteration, the ultrasound intensity is set to 1 / n (where n is the total number of samplings), and importance sampling is performed on each propagation ray in the above propagation ray set to obtain the set of important propagation rays.

[0037] The third step is to superimpose each important propagation ray in the above important propagation ray set to obtain a propagation fragment set.

[0038] As an example, each important propagation ray in the above-mentioned important propagation ray set is superimposed, all important propagation rays are integrated, and the intensity and propagation direction information of each important propagation ray are combined to finally generate a more comprehensive and accurate representation of the behavior of ultrasound in the tissue and obtain a propagation fragment set.

[0039] In some optional implementations of some embodiments, performing random texture sampling on each propagation segment in the propagation segment set to obtain an intensity distribution value of the ultrasonic wave on an imaging plane corresponding to the propagation segment set includes the following steps:

[0040] In the first step, for each of the above propagation fragments, the following generation steps are performed:

[0041] Sub-step 1: Sample propagation information from the propagation segments according to a preset step size to obtain a propagation information sequence. The preset step size may be a pre-set sampling step size. For each propagation segment, starting from the starting point of each propagation segment, stepping is performed with a preset step size, and random texture sampling is performed according to the material at the step point. This simulates the presence of microscopic particles in organ tissues, which can scatter ultrasound waves, thereby producing a texture with a noisy texture. The propagation information may be local segment information within the collected propagation segments. The duration between each piece of propagation information in the propagation information sequence is the preset step size.

[0042] Sub-step 2: Acquire the particle texture intensity information corresponding to each microstructure particle. Each microstructure particle has corresponding particle texture intensity information. The particle texture intensity information can be the texture intensity value corresponding to the microstructure particle.

[0043] Sub-step 3: For each propagation information in the propagation information sequence, determine the corresponding particle texture intensity information based on the random microscopic tissue particles corresponding to the propagation information, as the texture intensity information. In practice, based on the organ location and material of the propagation information, random sampling is performed from the set of matched microscopic tissue particles to determine the microscopic tissue particles corresponding to the propagation information.

[0044] In the second step, each texture intensity information sequence obtained is determined as an intensity distribution value.

[0045] In some optional implementations of some embodiments, performing an image processing task corresponding to the imaging screen based on the intensity distribution value to obtain a real-time ultrasound rendering screen of the simulated egg retrieval surgery at the current time may include the following steps:

[0046] The first step is to superimpose the intensity distribution values on the corresponding particle intensity matrix on the imaging screen to obtain the superimposed image. The sampling points are then projected onto the imaging plane for intensity superposition. Generating different textures also plays a key role in improving the realism of simulated ultrasound images.

[0047] In the second step, the superimposed image is convolved with a pre-set 2D convolution kernel to produce a convolved image. A 2D convolution operation is used as the point spread function. By adjusting the parameters of the convolution kernel, a more realistic ultrasound image texture can be obtained, closely resembling the visual quality observed in a clinical setting.

[0048] The third step is to mask and warp the convolution image to produce the real-time ultrasound rendering. Masking ensures that only diagnostically important areas are displayed. Warping transforms the initially obtained rectangular image into the characteristic sector-shaped observation area required in clinical practice.

[0049] In some optional implementations of some embodiments, particle texture intensity information is generated by the following steps:

[0050] The first step is to obtain a visual feature information set corresponding to microscopic tissue particles. The visual feature information in the visual feature information set corresponds one-to-one to the particle images in the particle image set corresponding to the microscopic tissue particles. The particle images can be photographic images of microscopic tissue particles. The visual feature information can be a summary of the visual feature information associated with each visual feature. Each visual feature can include particle size, shape, arrangement, and contrast. The visual feature information can be the characteristic content associated with each visual feature.

[0051] The second step is to perform Gaussian distribution fitting on each visual feature information in the above visual feature information set to obtain mean and variance parameters. The mean can be the feature mean information under each visual feature. The variance parameter can be the feature variance information under each visual feature.

[0052] In the third step, the particle texture intensity information is generated based on the mean and the variance parameter. As an example, the mean can be determined as the particle texture intensity information.

[0053] As another example, the execution entity may determine the particle texture intensity information using weighted values corresponding to the mean and variance parameters.

[0054] In some embodiments, the force feedback interaction hardware module is configured to utilize a force feedback device and a force feedback framework to perform force feedback processing based on probe data collected during the simulated egg retrieval procedure. The force feedback device and the force feedback framework are configured based on the operational characteristics of the simulated egg retrieval procedure. A force feedback device is a device that transmits physical interaction forces (such as resistance, pressure, and vibration) in a virtual or remote environment to a human hand in real time through a mechanical, electronic, or hydraulic system. In the medical field, it is primarily used to enhance a physician's tactile perception during surgery, diagnosis, or rehabilitation training, improving operational accuracy and safety. The force feedback framework is an integrated hardware and software system that supports the operation of the force feedback device, encompassing sensor data acquisition, force signal processing, feedback generation, and human-computer interaction logic. Its core goal is to achieve a closed "perception-computation-feedback" loop. The probe data can be probe operation data from an ultrasound probe collected during the simulated egg retrieval procedure. The force feedback processing can be the application of force to the ultrasound probe. Operational characteristics may include, but are not limited to, at least one of the following: minimally invasiveness, high precision, flexible anesthesia methods, and visual operation. For example, the force feedback device may be a Sensable PHANTOM Omni force feedback device, and the force feedback framework may be an OpenHaptics force feedback framework.

[0055] As an example, the tissue hardness of the currently touched tissue included in the probe data can be used to support providing multiple levels of force to the ultrasound probe to implement force feedback processing.

[0056] In some optional implementations of some embodiments, using a force feedback device and a force feedback framework, performing force feedback processing based on probe data during the above-mentioned simulated egg retrieval surgery may include the following steps:

[0057] Based on the force feedback device and force feedback framework, the following processing steps are performed:

[0058] Sub-step 1, in response to determining that the above-mentioned probe data is the offset deviation between the ultrasonic probe on the horizontal plane and the target origin set in the above-mentioned simulated egg retrieval operation, force feedback information is determined based on the above-mentioned offset deviation, and the force feedback direction corresponding to the above-mentioned force feedback information is set to the direction toward the above-mentioned target origin. The horizontal plane can be the xy plane in the three-dimensional coordinate system established for the egg retrieval target in the egg retrieval operation. The target origin can be the egg retrieval target. That is, the target origin can be the follicle position. The offset deviation can be the deviation value from the ultrasonic probe to the follicle position on the horizontal plane. There is corresponding force feedback information for each offset deviation on the horizontal plane. Among them, the force feedback information can be the magnitude of the force.

[0059] Sub-step 2: performing force feedback processing according to the force feedback direction corresponding to the force feedback information and the force feedback information.

[0060] In practice, a force in the force feedback direction is applied to the ultrasonic probe according to the magnitude of the stress corresponding to the force feedback information.

[0061] Sub-step 3, in response to determining that the above-mentioned probe data is the offset deviation between the ultrasonic probe on the vertical plane and the target origin set in the above-mentioned simulated egg retrieval surgery, and the offset deviation is less than the value of 0, setting maximum force feedback information, and the above-mentioned maximum force feedback information sets the force feedback direction to the target axis direction in the above-mentioned vertical platform. Wherein, the vertical plane can be the yz plane or the xz plane in the three-dimensional coordinate system established for the egg retrieval target in the egg retrieval surgery. The maximum force feedback information can be the maximum force that can be applied to the ultrasonic probe. The target axis direction can be the opposite direction of the z-axis.

[0062] Sub-step 4: performing force feedback processing on the stress feedback direction and the maximum force feedback information according to the maximum force feedback information.

[0063] In practice, the force in the force feedback direction is applied to the ultrasonic probe according to the stress magnitude corresponding to the maximum force feedback information.

[0064] Sub-step 5: In response to determining that the probe data is the yaw angle and pitch angle corresponding to the ultrasound probe, determine the angle deviation. The angle deviation can be the angle deviation of the yaw angle and the angle deviation of the pitch angle corresponding to the current ultrasound probe.

[0065] Sub-step 6: Determine the angle force feedback information corresponding to the angle deviation, and set the force feedback direction corresponding to the angle force feedback information to the opposite direction of the angle offset. The larger the angle deviation, the larger the corresponding angle force feedback information. That is, the angle deviation is proportional to the angle force feedback information.

[0066] Sub-step 7: performing force feedback processing according to the force feedback direction corresponding to the angle force feedback information and the angle force feedback information.

[0067] In practice, the force in the force feedback direction is applied to the ultrasonic probe according to the stress magnitude according to the angle force feedback information.

[0068] Sub-step 8: In response to determining that the probe data is rotation information corresponding to a rotation operation, determining pre-set rotational force information, and setting the force feedback direction corresponding to the rotational force information to the opposite direction of the rotation direction. The rotational information may be operation information for selecting an ultrasound probe. The rotational force information may be a fixed constraint torque set for the rotation operation.

[0069] Sub-step 9: performing force feedback processing according to the force feedback direction corresponding to the rotational force information and the rotational force information. In practice, force in the force feedback direction is applied to the ultrasonic probe according to the magnitude of the force corresponding to the rotational force information.

[0070] It should be noted that the aforementioned "steps of performing relevant processing based on a force feedback device and a force feedback framework," as one of the inventive features of this disclosure, address the problem of "inexperienced operators being unable to apply more accurate force to achieve the egg retrieval operation, which can easily lead to medical accidents." Based on this, this application utilizes a force feedback device and a force feedback framework to achieve adaptive control of various forces based on data from different types of probes, ensuring effective force application during the egg retrieval process, improving effective force control during the egg retrieval operation, and avoiding medical accidents during the egg retrieval process.

[0071] In some embodiments, the system function integration module is configured to render the real-time ultrasound image via a rendering thread, obtain force feedback data output by the force feedback interaction hardware module via a logic thread, and adjust the real-time ultrasound rendering image of the simulated egg retrieval surgery at the current time based on the force feedback data. In practice, the system is integrated and managed based on the QT framework, with the rendering thread and logic thread used to manage the image module and hardware module respectively, and data exchanged using a signal and slot model. The image module can be a real-time ultrasound image rendering module.

[0072] In some optional implementations of some embodiments, the system function integration module further includes: a preoperative learning module, a simulated surgery operation evaluation module, and a simulated surgery operation recording module. The preoperative learning module may be a module that provides surgical manipulation objects for preoperative learning. The simulated surgery operation evaluation module may be a module that evaluates the operation of the simulated surgery. The simulated surgery operation recording module may be a module that records the operation of the simulated surgery. And

[0073] The above-mentioned preoperative learning module is configured to: display the surgical operation process and precautions before the simulated egg retrieval operation to help the surgical operator quickly understand the operation skills.

[0074] The above-mentioned simulated surgical operation evaluation module is configured to: during the corresponding execution process of the simulated egg retrieval operation, evaluate the execution process according to clinical indicators, wherein the above-mentioned clinical indicators include: the number of follicles aspirated and the follicle aspiration rate, the operation time, prohibiting the needle from puncturing into organs other than the ovaries, and prohibiting negative pressure aspiration when the needle is outside the follicle area.

[0075] The above-mentioned simulated surgical operation recording module is configured to: after each execution process is completed, record the key indicator data of the execution process into a log file and generate operation improvement suggestions.

[0076] See also Figure 3 , shows a schematic diagram of a model scene in a simulation system used for oocyte retrieval surgery training. The model on the left is the pelvic cavity, and the model on the right is the follicle.

[0077] See also Figure 4 , which shows a schematic diagram of the ultrasound simulation egg retrieval process in a simulation system for egg retrieval surgery training.

[0078] See also Figure 5 , a schematic diagram showing the hardware setup in a simulation system for oocyte retrieval surgery training.

[0079] See also Figure 6Schematic diagrams of the uterus, bladder, and follicle aspiration in a simulation system used for oocyte retrieval surgery training are shown. The upper left diagram shows the uterus. The upper right diagram shows the bladder. The upper left and lower right diagrams show follicle aspiration.

[0080] See also Figure 7 , which shows a schematic diagram of operation prompts and warnings in a simulation system used for egg retrieval surgery training.

[0081] The various embodiments disclosed above have the following beneficial effects: Through the simulation system for egg retrieval surgery training of some embodiments of the present disclosure, the key operating steps and technical points of the egg retrieval surgery can be accurately and efficiently reproduced, effectively helping clinicians quickly master surgical techniques and providing patients with a better treatment experience. Based on this, the simulation system for egg retrieval surgery training of some embodiments of the present disclosure includes: a real-time ultrasound image rendering module, a force feedback interaction hardware module, and a system function integration module. The real-time ultrasound image rendering module is configured to: determine the propagation path and interaction of the ultrasound wave through the organ simulation model at the current time using sound wave propagation path tracing technology to obtain a set of propagation segments corresponding to the ultrasound wave; perform random texture sampling on each propagation segment in the propagation segment set to obtain the intensity distribution value corresponding to the microscopic tissue particles in the imaging plane corresponding to the propagation segment set; and perform image processing tasks corresponding to the imaging image based on the intensity distribution value to obtain a real-time ultrasound rendering image of the simulated egg retrieval surgery at the current time. Here, the real-time ultrasound image rendering module can simulate the propagation segment set in the organ simulation model using ultrasound technology. Random texture sampling is used to enhance the image intensity of microscopic tissue particles on the imaging plane, making the image plane more realistic and more closely resembling a realistic egg retrieval model. Furthermore, through image processing tasks, a real-time ultrasound rendering of the egg retrieval surgery at the current time is generated under ultrasound propagation, which is then presented to the clinician. The force feedback interaction hardware module is then configured to perform force feedback processing based on probe data from the simulated egg retrieval surgery using a force feedback device and a force feedback framework. The force feedback device and force feedback framework are configured based on the operational characteristics of the simulated egg retrieval surgery. The force feedback interaction hardware module effectively assists clinicians in precisely manipulating the probe during the simulated egg retrieval surgery, informing them through force how to correctly operate the probe, thereby achieving efficient egg retrieval during the procedure. Finally, the system function integration module is configured to render the real-time ultrasound image via a rendering thread, obtain force feedback data output by the force feedback interaction hardware module via a logic thread, and adjust the real-time ultrasound rendering of the simulated egg retrieval surgery at the current time based on this force feedback data. Here, through the system function integration module, precise control of the force feedback interaction hardware module and the real-time ultrasound image rendering module can be achieved, effective interaction between the two modules can be realized, and the normal execution of the simulated egg retrieval operation can be ensured.

[0082] Reference below Figure 2 , which shows a structural schematic diagram of an electronic device (eg, an electronic device) 200 suitable for implementing some embodiments of the present disclosure. Figure 2The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0083] like Figure 2 As shown, the electronic device 200 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 201, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 202 or a program loaded from a storage device 208 into a random access memory (RAM) 203. Various programs and data required for the operation of the electronic device 200 are also stored in the RAM 203. The processing device 201, the ROM 202, and the RAM 203 are connected to each other via a bus 204. An input / output (I / O) interface 205 is also connected to the bus 204.

[0084] Typically, the following devices may be connected to the I / O interface 205: an input device 206 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 207 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 208 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 209. The communication device 209 may allow the electronic device 200 to communicate with other devices wirelessly or by wire to exchange data. Figure 2 The electronic device 200 is shown with various devices, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead. Figure 2 Each block shown in the figure may represent one device, or may represent multiple devices as needed.

[0085] In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from a network via the communication device 209, or installed from the storage device 208, or installed from the ROM 202. When the computer program is executed by the processing device 201, the above-mentioned functions defined in the method of some embodiments of the present disclosure are performed.

[0086] It should be noted that in some embodiments of the present disclosure, the computer-readable medium mentioned above may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In some embodiments of the present disclosure, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device, or device. In some embodiments of the present disclosure, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.

[0087] In some embodiments, the client and server can communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol), and can be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0088] The computer-readable medium may be included in the electronic device, or may exist independently and not be incorporated into the electronic device. The computer-readable medium carries one or more programs. When executed by the electronic device, the electronic device: determines the propagation path and interaction of ultrasound waves through the organ simulation model at the current time using acoustic wave propagation path tracing technology to obtain a set of propagation segments corresponding to the ultrasound waves; performs random texture sampling on each propagation segment in the set of propagation segments to obtain intensity distribution values corresponding to microscopic tissue particles in the imaging plane corresponding to the propagation segment set; and performs image processing tasks corresponding to the imaging screen based on the intensity distribution values to obtain a real-time ultrasound rendering of the simulated egg retrieval surgery at the current time. Force feedback processing is performed using a force feedback device and a force feedback framework based on probe data during the execution of the simulated egg retrieval surgery, wherein the force feedback device and the force feedback framework are configured based on the corresponding operational characteristics of the simulated egg retrieval surgery. The above-mentioned real-time ultrasound image is rendered through the rendering thread, and the force feedback data output by the force feedback interaction hardware module is obtained through the logic thread, so as to adjust the real-time ultrasound rendering image of the simulated egg retrieval operation at the current time according to the above-mentioned force feedback data.

[0089] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages such as Java, Smalltalk, C++, and conventional procedural programming languages such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0090] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0091] The units described in some embodiments of the present disclosure may be implemented in software or hardware, and may also be provided in a processor.

[0092] The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, and without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0093] The above description is only an illustration of some preferred embodiments of the present disclosure and the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the above-mentioned inventive concept. For example, the above-mentioned features are replaced with (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A simulation system for egg retrieval surgery training, comprising: Real-time ultrasound image rendering module, force feedback interaction hardware module, and system function integration module, including: The real-time ultrasound image rendering module is configured to: determine the propagation path and interaction of ultrasound waves through the organ simulation model at the current time through the sound wave propagation path tracing technology to obtain a propagation segment set corresponding to the ultrasound waves; perform random texture sampling on each propagation segment in the propagation segment set to obtain an intensity distribution value corresponding to microscopic tissue particles of the ultrasound waves in the imaging plane corresponding to the propagation segment set; and perform image processing tasks corresponding to the imaging image based on the intensity distribution value to obtain a real-time ultrasound rendering image of the simulated egg retrieval surgery at the current time; The force feedback interaction hardware module is configured to: utilize a force feedback device and a force feedback framework to perform force feedback processing according to probe data during the execution of the simulated egg retrieval surgery, wherein the force feedback device and the force feedback framework are configured based on operational characteristics corresponding to the simulated egg retrieval surgery; The system function integration module is configured to: render the real-time ultrasound image through a rendering thread, obtain force feedback data output by the force feedback interaction hardware module through a logic thread, and adjust the real-time ultrasound rendering image of the simulated egg retrieval surgery at the current time according to the force feedback data.

2. The method according to claim 1, wherein The acoustic wave propagation path tracing technology is used to determine the propagation path and interaction of the ultrasonic wave through the organ simulation model at the current time, and obtain a propagation segment set corresponding to the ultrasonic wave, including: By using the sound wave propagation path tracing technology, the propagation path and interaction of the ultrasound wave through the organ simulation model at the current time are determined to obtain the propagation ray set; performing importance sampling on each propagation ray in the propagation ray set to obtain an important propagation ray set; The important propagation rays in the important propagation ray set are superimposed to obtain a propagation segment set.

3. The method according to claim 1, wherein The performing random texture sampling on each propagation segment in the propagation segment set to obtain an intensity distribution value of the ultrasonic wave on an imaging plane corresponding to the propagation segment set includes: For each of the propagation segments, the following generation steps are performed: Sampling propagation information from the propagation segment according to a preset step size to obtain a propagation information sequence; Obtaining the texture intensity information of each particle corresponding to each microstructure particle; For each propagation information in the propagation information sequence, determining corresponding particle texture intensity information according to the random microstructure particles corresponding to the propagation information as texture intensity information; The obtained texture intensity information sequences are determined as intensity distribution values.

4. The method according to claim 1, wherein The performing of an image processing task corresponding to the imaging screen based on the intensity distribution value to obtain a real-time ultrasound rendering screen of the simulated egg retrieval surgery at the current time includes: Superimposing the intensity distribution values on the particle intensity matrix corresponding to the imaging screen to obtain a superimposed screen; Using a preset two-dimensional convolution kernel, convolution processing is performed on the superimposed image to obtain a convolution image; Performing image masking and image deformation on the convolution picture to obtain the real-time ultrasound rendering picture.

5. The method according to claim 1, wherein The system function integration module also includes: a preoperative learning module, a simulated surgical operation evaluation module, and a simulated surgical operation recording module; and The preoperative learning module is configured to: display the surgical operation process and precautions before the simulated egg retrieval operation to help the surgical subject quickly understand the operation skills; The simulated surgical operation evaluation module is configured to: during the execution of the simulated egg retrieval operation, evaluate the execution process according to clinical indicators, wherein the clinical indicators include: the number of follicles aspirated and the follicle aspiration rate, the operation time, prohibiting the needle from puncturing organs other than the ovary, and prohibiting negative pressure aspiration when the needle is outside the follicle area; The simulated surgery operation recording module is configured to: after each execution process is completed, record the key indicator data of the execution process into a log file and generate operation improvement suggestions.

6. The method according to claim 3, wherein: The particle texture intensity information is generated by the following steps: Obtaining a visual feature information set corresponding to microscopic tissue particles; Performing Gaussian distribution fitting on each visual feature information in the visual feature information set to obtain mean and variance parameters; The particle texture intensity information is generated according to the mean and the variance parameter.

7. An electronic device comprising: one or more processors; a storage device having one or more programs stored thereon, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

8. A computer-readable medium having a computer program stored thereon, wherein: When the program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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