Method for processing surgical smoke, medical system and computer device

Abstract

The present specification provides a surgical smoke processing method, a medical system and a computer device. Based on the method, before the operation is performed, the associated information of a target surgical instrument to be used and the associated information of a target organ to be operated can be acquired first; then, according to the associated information of the target surgical instrument and the associated information of the target organ, a matched first control parameter is determined; and then, according to the first control parameter, the smoke exhaust device can be started and controlled in the standby state in advance. During the operation, the smoke feature data can be determined in real time or at a fixed time according to the surgical image in the operation process; and then, according to the smoke feature data and the first control parameter, the smoke exhaust device is controlled to perform smoke removal processing. Thus, the smoke generated during the operation can be intelligently and accurately identified and automatically removed, the interference of the smoke on the operation field of view is effectively reduced, and the operation risk is reduced.

Description

Technical Field

[0001] This manual belongs to the field of medical robot technology, and in particular relates to methods for handling surgical fumes, medical systems, and computer equipment. Background Technology

[0002] During surgery, the use of surgical instruments for electrocoagulation or electrocautery often generates a large amount of smoke, which can interfere with the surgeon's field of vision and increase surgical risks.

[0003] Based on existing methods, most procedures require doctors to first manually determine whether smoke is present via a display screen; if smoke is detected, they then manually operate equipment such as insufflators to remove it. In practice, these methods are often cumbersome, lack intelligence, and have poor smoke removal effectiveness, making them prone to errors and affecting the normal progress of the surgery.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This manual provides a method, medical system, and computer device for handling surgical smoke, which can intelligently and accurately identify and automatically remove smoke generated during surgery, effectively reducing the interference of smoke with the surgical field of vision and lowering surgical risks.

[0006] This specification provides a method for handling surgical smoke, including: acquiring the association information of a target surgical instrument and the association information of a target organ to be operated on; determining a matching first control parameter based on the association information of the target surgical instrument and the association information of the target organ; and activating and controlling a smoke extraction device to be in standby mode based on the first control parameter, so as to perform smoke removal processing when smoke is detected during the operation.

[0007] This specification also provides a method for processing surgical smoke, comprising: acquiring surgical images during the surgical process; acquiring effective image features based on the surgical images; wherein the effective image features include at least two of the following: grayscale value, mode grayscale value, median grayscale value, average grayscale value, grayscale value variance, area ratio, perimeter ratio, and grayscale value distribution ratio of the image; and controlling the smoke extraction device to perform corresponding smoke removal processing during the surgical process based on the effective image features.

[0008] This specification also provides a medical system, including: a surgical smoke treatment device, an endoscope, a chip reading unit, and a smoke extraction device. The chip reading unit is used to acquire the association information of the target surgical instruments, the endoscope is used to acquire the association information of the target organ to be operated on, and the surgical smoke treatment device is used to control the smoke extraction device to remove smoke during the operation based on the association information of the target surgical instruments and the association information of the target organ, using the surgical smoke treatment method.

[0009] This specification also provides a computer device including a processor and a memory for storing processor-executable instructions, wherein the processor executes the instructions to implement the relevant steps of the surgical smoke treatment method.

[0010] This specification also provides a computer-readable storage medium having computer instructions stored thereon, which, when executed, implement the relevant steps of the surgical smoke treatment method.

[0011] Based on the surgical smoke treatment method, medical system, and computer equipment provided in this manual, before surgery, the association information of the target surgical instruments and the target organ to be operated on can be obtained first. Then, based on the association information of the target surgical instruments and the target organ, matching first control parameters can be determined. Subsequently, the smoke extraction equipment can be pre-activated and kept in standby mode according to the first control parameters. During the actual surgery, the current smoke characteristic data can be determined by real-time or periodic acquisition and based on surgical images during the procedure. Then, based on the current smoke characteristic data and the first control parameters, the smoke extraction equipment can be controlled to perform the current smoke removal process. This allows for intelligent and accurate identification and automatic removal of smoke generated during surgery, effectively reducing smoke interference with the surgical field of view and lowering surgical risks. Furthermore, by using a preset smoke prediction model to process the association information of the target surgical instruments and the target organ, the possibility of smoke generation during the upcoming surgery, as well as the possible concentration and range of smoke, can be predicted in advance. This allows for accurate determination of appropriate first control parameters to pre-control the smoke extraction power of the smoke extraction equipment. Furthermore, by acquiring surgical images during the operation and extracting multiple effective image features from these images, and then based on statistical principles, combining multiple effective image features and conducting multidimensional analysis, a suitable second control parameter can be accurately determined. This allows for timely and flexible adjustment of the current smoke exhaust power of the smoke exhaust equipment, resulting in a relatively better smoke exhaust effect. Attached Figure Description

[0012] To more clearly illustrate the embodiments of this specification, the accompanying drawings used in the embodiments will be briefly introduced below. The drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a schematic flowchart of a surgical smoke treatment method provided in one embodiment of this specification;

[0014] Figure 2 This is a schematic diagram of one embodiment of the surgical fume treatment method provided in the embodiments of this specification applied in a medical system;

[0015] Figure 3 This is a schematic diagram of the structural components of the patient's surgical platform;

[0016] Figure 4 This is a schematic diagram of the structural components of the target surgical instrument;

[0017] Figure 5 This is a schematic diagram of an embodiment for reading chip information from the storage chip of a surgical instrument;

[0018] Figure 6 This is a schematic diagram illustrating an embodiment of determining smoke feature data using the surgical smoke processing method provided in this specification, within a specific scenario example.

[0019] Figure 7 This is a schematic diagram of an embodiment in which the surgical smoke processing method provided in the embodiments of this specification is applied to adjust and update the relevant model using feedback data in a scenario example;

[0020] Figure 8 This is a flowchart illustrating a method for treating surgical fumes according to another embodiment of this specification;

[0021] Figure 9 This is a schematic diagram of the structural composition of a computer device provided in one embodiment of this specification;

[0022] Figure 10 This is a schematic diagram of the structural composition of a medical system provided in one embodiment of this specification;

[0023] Figure 11 This is a schematic diagram of the structural composition of a surgical smoke treatment device provided in one embodiment of this specification. Detailed Implementation

[0024] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0025] See Figure 1 As shown in the embodiments of this specification, a method for treating surgical fumes is provided. In specific implementation, this method may include the following:

[0026] S101: Obtain the association information of the target surgical instrument and the association information of the target organ to be operated on;

[0027] S102: Determine the matching first control parameter based on the association information of the target surgical instrument and the association information of the target organ;

[0028] S103: Based on the first control parameter, start and control the smoke exhaust equipment to be in standby mode so as to perform smoke removal when smoke is detected during the operation.

[0029] In some embodiments, the aforementioned target surgical instrument can be specifically understood as the surgical instrument to be used during the surgery. The aforementioned target organ can be specifically understood as the organ or tissue to be operated on.

[0030] The aforementioned smoke can be understood as the smoke generated by surgical instruments during the operation due to electrocoagulation or electroresection. This type of smoke can interfere with the surgeon's field of vision, thereby increasing the surgical risk for the patient.

[0031] The aforementioned first control parameter can be understood as the control parameter used to control the smoke exhaust equipment. Specifically, the smoke exhaust power of the smoke exhaust equipment can be controlled based on the aforementioned first control parameter. Furthermore, the smoke exhaust direction, smoke exhaust velocity, etc., of the smoke exhaust equipment can also be controlled based on the aforementioned first control parameter.

[0032] Based on the surgical smoke handling method provided in this manual, before performing specific surgery on a patient's target organ using the target surgical instrument, the doctor can obtain and predict the possible smoke situation during the surgery in advance based on the association information of the target surgical instrument and the association information of the target organ. In this way, the doctor can determine the first control parameter for the smoke situation in advance and start the smoke exhaust device in advance according to the first control parameter so that the smoke generated during the surgery can be removed in time.

[0033] In some embodiments, see details. Figure 2 As shown, the above-described method for handling surgical fumes can be specifically applied to one side of the medical system. Doctors can then use this medical system to perform surgical procedures on patients.

[0034] For details, please refer to Figure 2 As shown, the aforementioned medical system includes at least a patient-facing surgical platform (or patient-end control device) and a doctor-facing console (or doctor-end control device). Specifically, the doctor can control the patient surgical platform through the doctor's console to perform surgery on the patient.

[0035] Among them, see Figure 3 As shown, the aforementioned patient surgical platform can be configured with multiple robotic arms (or tool arms). At least one of the robotic arms on the patient surgical platform carries the target surgical instrument for performing the surgical procedure.

[0036] See Figure 4 As shown, the aforementioned target surgical instrument may include: a first end (also called the proximal control section), a long rod, and a second end (also called the distal control section). The first end is connected to the patient's surgical platform and contains an embedded storage chip. See reference... Figure 5 As shown, the aforementioned memory chip can specifically store hardware information related to the target surgical instrument, such as the instrument type, electrosurgical energy level, service life, manufacturing date, instrument ID number (or ID code), usage duration, number of uses, etc. The second end is configured with specific hardware instruments for surgery, such as duckbill forceps, rat-tooth forceps, and powerful duckbill forceps.

[0037] Smoke extraction equipment can also be mounted on the robotic arm carrying the target surgical instruments, or other robotic arms. Specifically, this smoke extraction equipment can include a smoke exhaust duct system. This smoke extraction equipment can be used to remove surrounding smoke.

[0038] Furthermore, the aforementioned patient surgery platform is also connected to the doctor's control console. Doctors can control the target surgical instruments on the patient surgery platform's robotic arms to perform specific surgical procedures via the control console.

[0039] Furthermore, at least one of the multiple robotic arms on the patient surgical platform can be equipped with an image acquisition unit such as an endoscope or camera. This image acquisition unit can extend into the surgical environment (e.g., the abdominal cavity of a patient undergoing surgery) and connect to the surgeon's console. Thus, surgical images during the procedure can be acquired in real-time or at set intervals and transmitted to the surgeon's console for processing and display.

[0040] Based on the aforementioned medical system, before performing surgery, the doctor can obtain the association information of the target surgical instruments and the target organ through the doctor control platform. By combining the association information of the target surgical instruments and the target organ, the doctor can predict the possible smoke situation during the surgery. Based on the predicted smoke situation, the doctor can determine the matching first control parameter. Then, based on the first control parameter, the doctor can start the smoke extraction device in advance through the doctor's console and put the smoke extraction device into standby mode.

[0041] During surgery, doctors can also acquire surgical images in real time or at set intervals using the image acquisition unit. By analyzing and identifying these images, they can accurately determine the current smoke situation. Based on the current smoke situation, they can determine the matching second control parameters. Then, they can flexibly control the smoke extraction equipment based on both the first and second control parameters to more accurately and effectively remove smoke from the surgical environment.

[0042] In some embodiments, the association information of the target surgical instrument can be specifically understood as information related to the target surgical instrument to be used. Specifically, the association information of the target surgical instrument may include at least one of the following: the instrument type of the target surgical instrument, the electrosurgical energy level of the target surgical instrument, the lifespan information of the target surgical instrument, etc.

[0043] The specific types of the aforementioned target surgical instruments may include at least one of the following: duckbill grasping forceps, rat tooth grasping forceps, powerful duckbill grasping forceps, etc.

[0044] The electrosurgical energy levels of the aforementioned target surgical instruments can specifically include: Level 1, Level 2, Level 3, etc. The specific energy level of the target surgical instrument can be set by the physician user based on specific circumstances and usage needs.

[0045] In some embodiments, the above-mentioned acquisition of the association information of the target surgical instrument may specifically include: reading the chip information of the storage chip of the target surgical instrument; and acquiring the association information of the target surgical instrument based on the chip information.

[0046] Specifically, a chip reading unit can be installed at the mounting and connection point of the robotic arm. When a target surgical instrument is detected mounted on the robotic arm, the chip reading unit can be triggered to identify and read the storage chip in the first end of the target surgical instrument to obtain the associated information of the target surgical instrument.

[0047] Specifically, the memory chip can store information related to the target surgical instrument in the form of an identification code. Correspondingly, the chip reading unit can obtain the relevant identification code as chip information by reading the memory chip; then, according to the identification code lookup table, it processes the chip information to obtain the associated information of the target surgical instrument.

[0048] In some embodiments, the associated information of the target surgical instrument may further include the lifespan information of the target surgical instrument. Specifically, the lifespan information may include: service life and usage duration. Correspondingly, the method may further include: determining whether the usage duration of the target surgical instrument has exceeded its service life based on its service life and usage duration; and, if it is determined that the usage duration of the target surgical instrument has exceeded its service life, prompting the physician to replace the surgical instrument to reduce surgical risks.

[0049] In some embodiments, if it is determined that the usage time of the target surgical instrument has exceeded its service life, after prompting the doctor to replace the surgical instrument, the medical system may not trigger the above-described surgical smoke processing method until it detects that the doctor has replaced and installed a surgical instrument whose usage time has not exceeded its service life. Conversely, if it is determined that the usage time of the target surgical instrument has not exceeded its service life, the medical system may normally trigger the above-described surgical smoke processing method.

[0050] In some embodiments, the duration of use of surgical instruments also affects the amount of smoke generated during surgery. For example, when surgical instruments are used for a long time, or even near their lifespan, some components of the instruments may have aged, leading to the generation of more smoke during surgery. Therefore, to more accurately predict smoke levels and determine a suitable first control parameter, lifespan information can be obtained as association information for the target surgical instrument. This association information, containing lifespan information, can then be combined with the association information for the target organ to predict smoke levels and determine a more appropriate first control parameter in advance.

[0051] In some embodiments, the association information of the target organ can be specifically understood as information related to the target organ to be operated on. Specifically, the association information of the target organ may include: organ type and / or lesion information of the target organ, etc.

[0052] In some embodiments, the acquisition of the association information of the target organ described above may specifically include: acquiring an organ image of the target organ to be operated on; and performing image recognition on the organ image to obtain the association information of the target organ.

[0053] Specifically, a robotic arm equipped with an image acquisition unit can be controlled to first extend into the surgical environment and take pictures of the target organ to be operated on, so as to obtain an organ image of the target organ.

[0054] Specifically, the above-mentioned image recognition of the organ image to obtain the association information of the target organ may include: processing the organ image using a preset image recognition model to obtain the corresponding recognition result; and determining the association information of the target organ based on the recognition result.

[0055] Specifically, the aforementioned preset image recognition model can be understood as an image algorithm model that can identify and output data such as organ type and lesion information of organs in the input image as recognition results.

[0056] Specifically, the aforementioned preset image recognition model can be trained in the following way: obtain sample images containing organs; and label the organ types and lesion information in the sample images to obtain labeled sample images; use the labeled sample images to train the model to obtain the preset image recognition model.

[0057] In some embodiments, see Figure 7 As shown above, based on the association information of the target surgical instrument and the association information of the target organ, a matching first control parameter is determined. In specific implementation, this may include the following:

[0058] S1: Combine the association information of the target surgical instruments and the association information of the target organs to obtain the target combination data;

[0059] S2: By processing the target combination data using a preset smoke prediction model, the corresponding prediction results are obtained;

[0060] S3: Based on the prediction results, determine the first matching control parameter.

[0061] Specifically, the aforementioned preset smoke prediction model can be understood as a neural network model that can predict whether the surgery to be performed will produce smoke, as well as the concentration, range, and other smoke conditions, based on the input combination data.

[0062] For specific implementation, please refer to Figure 7As shown, the association information of the target surgical instruments and the association information of the target organs can be concatenated to obtain corresponding target combination data. This target combination data is then input into a preset smoke prediction model, which is run to obtain the corresponding prediction results. Furthermore, based on the prediction results, the smoke conditions during the future surgery can be determined. Further, based on the performance parameters of the smoke extraction equipment, a smoke extraction power matching the aforementioned smoke conditions can be determined; then, based on the smoke extraction power, control parameters for the smoke extraction equipment are determined as the first control parameter.

[0063] Based on the above embodiments, a preset smoke prediction model can be used to predict the future smoke situation of the surgery by processing the correlation information of the target instruments and the correlation information of the target organs obtained before the surgery; then, based on the above smoke situation, the first control parameters for controlling the smoke exhaust equipment can be accurately determined in advance.

[0064] In some embodiments, the preset smoke prediction model may be specifically constructed in advance by training the model using historical surgical fogging records.

[0065] In practice, historical surgical fumigation records can be collected first, and the association information of historical surgical instruments used when surgical fumigation was required in the past, as well as the association information of historical organs targeted in the surgery, can be extracted from these records. The association information of historical surgical instruments and historical organs can be combined to obtain historical sample data. At the same time, based on the historical surgical fumigation records, the fumigation situation corresponding to the above historical sample data can be determined. The historical sample data can be labeled according to the fumigation situation to obtain labeled historical sample data. The labeled historical sample data can then be used to train the model to obtain the preset fumigation prediction model.

[0066] In addition, based on historical surgical fumigation records, the fumigation power and control parameters used by the fumigation equipment for different fumigation conditions can be extracted. Then, based on the above data, a mapping relationship between the fumigation power and control parameters of the fumigation equipment for different fumigation conditions can be constructed.

[0067] Accordingly, in specific implementation, the target combination data can be processed first using a preset smoke prediction model to obtain the corresponding prediction results; the smoke situation can be determined based on the prediction results; and then, based on the smoke situation and the above mapping relationship, the matching control parameters can be determined as the first control parameters.

[0068] In some embodiments, in addition to acquiring the association information of the target surgical instruments and the target organ, environmental information of the target surgery can also be acquired. This environmental information may specifically include one or more of the following: surgery type, temperature, humidity, etc. Accordingly, by combining this environmental information, the future smoke conditions of the upcoming surgery can be predicted more accurately in advance.

[0069] In some embodiments, in addition to obtaining the association information of the target surgical instruments and the target organs, custom parameters defined by the physician user can also be obtained. These custom parameters may specifically include surgical smoke prediction values ​​set by the physician user based on experience, such as "no smoke," "low smoke," or "high smoke." Accordingly, by combining these custom parameters and fully utilizing the physician user's surgical experience, the future smoke situation of the upcoming surgery can be predicted more accurately in advance.

[0070] In some embodiments, during implementation, a corresponding control command can be generated first based on the first control parameter; then, the smoke extraction device can be started in advance according to the control command, and the smoke extraction device can be controlled to be in standby mode. Furthermore, during the surgical procedure, when smoke is detected, the smoke extraction device can be controlled to perform smoke removal according to the first control parameter.

[0071] In some embodiments, after the smoke extraction device is started and controlled to be in standby mode according to the first control parameter, the method may further include the following:

[0072] S1: Acquire surgical images during the surgical procedure;

[0073] S2: Determine smoke feature data based on surgical images;

[0074] S3: Based on the smoke characteristic data and the first control parameter, control the smoke exhaust equipment to perform corresponding smoke removal treatment.

[0075] Specifically, the aforementioned smoke characteristic data can be understood as characteristic data that reflects the smoke situation. Specifically, the aforementioned smoke characteristic data may include: smoke concentration, and / or, smoke range, etc.

[0076] Furthermore, the aforementioned smoke characteristic data may also include: the direction of smoke diffusion, the speed of smoke diffusion, etc.

[0077] In practice, the image acquisition unit mounted on the robotic arm can be controlled in real time or at regular intervals (e.g., every 30 seconds) to acquire current surgical images during the operation. Then, based on the current surgical images, image analysis can be used to determine the corresponding smoke characteristic data, thus obtaining the current actual smoke situation. Furthermore, based on the current actual smoke situation, the previously determined first control parameters can be used to more precisely control the smoke extraction equipment to perform the current smoke removal process.

[0078] In some embodiments, the determination of smoke feature data based on surgical images may, in specific implementations, include:

[0079] S1: Based on the surgical image, obtain effective image features; wherein, the effective image features include at least one of the following: gray value, mode gray value, median gray value, average gray value, gray value variance, area ratio, perimeter ratio, gray value distribution ratio, etc.

[0080] S2: Determine smoke feature data based on valid image features.

[0081] The aforementioned effective image features can be selected from a large number of historical surgical defogging records to effectively reflect the smoke situation. In practice, depending on the specific circumstances and processing requirements, other suitable image features can be further introduced as the aforementioned effective image features.

[0082] In practice, feature processing can be performed on surgical images to extract the aforementioned effective image features. Then, based on statistical theory, these effective image features can be comprehensively utilized, combined with multiple dimensional attributes, and multi-dimensional analysis can be performed to determine data such as the concentration of smoke in the surgical environment, thus obtaining smoke feature data.

[0083] Specifically, when determining smoke characteristic data, refer to... Figure 6 As shown, smoke feature data can be determined by processing effective image features using a pre-defined image multi-dimensional analysis model. Specifically, the pre-defined image multi-dimensional analysis model can be an algorithm model constructed in advance based on statistical analysis of historical surgical defogging records.

[0084] In some embodiments, the control of the smoke exhaust equipment to perform corresponding smoke removal processing based on the smoke characteristic data and the first control parameter may include the following:

[0085] S1: Determine whether smoke exists based on the smoke characteristic data;

[0086] S2: If smoke is confirmed to be present, the smoke exhaust equipment is controlled to perform corresponding smoke removal treatment based on the smoke characteristic data and the first control parameter.

[0087] Specifically, based on the smoke concentration in the smoke characteristic data, it can be detected whether the current smoke concentration is greater than a preset lower limit value; when it is determined that the current smoke concentration is greater than the preset lower limit value, it can be determined that the smoke is currently stored; then, the smoke characteristic data and the first control parameter can be used to control the smoke exhaust equipment to perform smoke removal treatment in a timely manner.

[0088] In some embodiments, when performing smoke removal, the smoke extraction device can be directly controlled to remove the existing smoke according to the first control parameter; alternatively, the control parameter can be adjusted according to the smoke characteristic data, and then the smoke extraction device can be controlled to remove the existing surgical smoke according to the adjusted control parameter.

[0089] In some embodiments, the control of the smoke exhaust equipment to perform corresponding smoke removal processing based on the smoke characteristic data and the first control parameter may include the following:

[0090] S1: Determine the matching second control parameter based on the smoke characteristic data;

[0091] S2: Detect whether the second control parameter meets the preset parameter threshold range; wherein, the preset parameter threshold range is determined based on the first control parameter;

[0092] S3: If the second control parameter meets the preset parameter threshold range, control the smoke exhaust equipment to perform corresponding smoke removal treatment according to the first control parameter.

[0093] In some embodiments, determining the matching second control parameter based on smoke feature data may specifically include: processing the smoke feature data using a preset smoke matching model to obtain the second control parameter.

[0094] Specifically, when the smoke characteristic data includes the direction of smoke diffusion, the second control parameter may also include other types of parameters that are different from the first control parameter, such as the clearing angle.

[0095] Specifically, the preset smoke matching model can be understood as an algorithm model that can determine and output appropriate control parameters for smoke exhaust equipment based on the input smoke feature data.

[0096] Before implementation, the preset smoke matching model can be trained in the following way: extract historical smoke feature data and historical control parameters corresponding to the historical smoke feature data based on historical surgical fogging records; combine the historical smoke feature data and historical control parameters to obtain combined sample data; train the preset smoke matching model based on the combined sample data.

[0097] In addition, in specific implementation, the corresponding smoke conditions can be determined based on smoke characteristic data; then, based on the smoke conditions and the mapping relationship, a matching second control parameter can be determined.

[0098] In some embodiments, the preset parameter threshold range can be specifically understood as the range of adjacent data values ​​of the first control parameter. Specifically, the preset parameter threshold range can be determined based on the first control parameter and the error tolerance.

[0099] In some embodiments, when it is determined that the second control parameter falls within a preset parameter threshold range, it can be determined that the first control parameter is still applicable to the current smoke conditions, and the smoke extraction device can continue to be controlled to perform the current smoke removal process according to the first control parameter. Conversely, when it is determined that the second control parameter does not fall within the preset parameter threshold range, it can be determined that the first control parameter is no longer applicable to the current smoke conditions, and the second control parameter can be used to control the smoke extraction device to perform the current smoke removal process.

[0100] In some embodiments, after detecting whether the second control parameter meets a preset parameter threshold range, the method may further include: if it is determined that the second control parameter does not meet the preset parameter threshold range, controlling the smoke exhaust device to perform corresponding smoke removal processing according to the second control parameter.

[0101] In some embodiments, the above-mentioned control of the smoke exhaust equipment to perform corresponding smoke removal treatment according to the second control parameter may include the following:

[0102] S1: Based on the second control parameter, the corresponding control command is encapsulated;

[0103] S2: The control command is sent to the smoke exhaust unit; wherein, the smoke exhaust unit is connected to the smoke exhaust equipment; the smoke exhaust unit is used to verify the control command; if the verification is successful, the smoke exhaust unit controls the smoke exhaust equipment to perform smoke exhaust operation according to the control command.

[0104] Specifically, the second control parameter can be encapsulated into a corresponding control command according to the corresponding encapsulation protocol; and then the control command can be sent to the smoke exhaust unit according to the corresponding transmission protocol.

[0105] The smoke exhaust unit is connected to the smoke exhaust equipment and is used to receive and parse control commands to obtain control parameters; in response to control commands, it controls the smoke exhaust equipment based on the control parameters.

[0106] Specifically, the above-mentioned verification of control commands may include: verifying the legality of control commands according to preset protocol rules in order to avoid receiving or misresponding to other interfering commands.

[0107] Specifically, verifying the legality of control commands can include verifying the identification information of the source of the control command.

[0108] If the legality verification is successful, the control parameters carried by the control command can be further verified for security to ensure that the control parameters carried by the control command are safe and reliable.

[0109] Specifically, verifying the security of control commands can include detecting whether the control parameters carried by the control commands fall within a preset security threshold range.

[0110] In some embodiments, if the smoke exhaust unit determines that the control command verification has passed, it may respond to the control command and control the smoke exhaust device to perform the current smoke exhaust operation according to the second control parameter; conversely, if the smoke exhaust unit determines that the control command verification has failed, it may not respond to the control command, but continue to control the smoke exhaust device to perform the current smoke exhaust operation according to the first control parameter, and wait for the next control command.

[0111] In some embodiments, after controlling the smoke extraction device to perform corresponding smoke removal processing based on the smoke characteristic data and the first control parameters, the method may further include: receiving feedback data from doctor users; and adjusting and updating the model used based on the feedback data.

[0112] Specifically, a corresponding database can be created in the storage device connected to the medical system. This database can store the associated information of the target surgical instruments acquired each time, organ images of the target organ, surgical images, and feedback data. Simultaneously, relevant models, such as preset smoke prediction models and preset smoke matching models, as well as historical surgical fogging records, can also be stored in the database.

[0113] In addition, the database can be periodically cleaned of expired target surgical instrument association information, target organ images, and surgical images, and only the target surgical instrument association information, target organ images, and surgical images obtained in the most recent few times (e.g., the most recent 3 times) can be retained in the database to avoid data redundancy.

[0114] In practice, after each surgery completed using the aforementioned medical system, the doctor's console can prompt the doctor to evaluate the smoke extraction effect of the surgery and receive the evaluation data input by the doctor as the aforementioned feedback data. Furthermore, the feedback data can be used to determine whether the smoke extraction effect meets the user's requirements. If the smoke extraction effect does not meet the user's requirements, the feedback data can be analyzed to obtain analysis results. Based on the analysis results, relevant models stored in the database, such as preset smoke prediction models and preset smoke matching models, as well as other relevant data, can be adjusted and updated in a targeted manner, thereby continuously improving the smoke extraction effect.

[0115] As can be seen from the above, based on the surgical smoke processing method provided in the embodiments of this specification, before surgery, the association information of the target surgical instrument to be used and the association information of the target organ to be operated on can be obtained first; then, based on the association information of the target surgical instrument and the target organ, a matching first control parameter can be determined; and then, based on the first control parameter, the smoke extraction device can be started in advance and controlled to be in standby mode. During surgery, smoke characteristic data can be determined by collecting and analyzing surgical images during the surgery in real time or at regular intervals; then, based on the smoke characteristic data and the first control parameter, the smoke extraction device can be controlled to perform smoke removal. This enables intelligent and accurate identification and automatic removal of smoke generated during surgery, effectively reducing the interference of smoke on the surgical field and lowering surgical risks. Furthermore, by using a preset smoke prediction model to process the association information of the target surgical instrument and the target organ, it is possible to predict in advance whether smoke may occur during the surgery to be performed, as well as the possible concentration and range of smoke, and thus accurately determine the appropriate first control parameter to pre-control the smoke extraction power of the smoke extraction device. Furthermore, by acquiring surgical images during the operation and extracting multiple effective image features from these images, and then, based on statistical principles and by integrating these multiple effective image features through multi-dimensional analysis, a suitable second control parameter is accurately determined, allowing for timely and flexible adjustment of the current smoke extraction power of the smoke extraction equipment. This results in a relatively better smoke extraction effect.

[0116] See Figure 8 As shown, this manual also provides another method for treating surgical fumes, which may include the following:

[0117] S801: Acquire surgical images during the surgical procedure;

[0118] S802: Based on the surgical image, obtain effective image features; wherein, the effective image features include at least two of the following: gray value, mode gray value, median gray value, average gray value, gray value variance, area ratio, perimeter ratio, and gray value distribution ratio of the image;

[0119] S803: Based on the effective image features, control the smoke extraction device to perform corresponding smoke removal processing during the operation.

[0120] Based on the above embodiments, in specific implementation, at least two effective image features can be extracted from the surgical images to accurately determine the current smoke feature data; then, the presence of smoke can be determined based on the current smoke feature data, and if smoke is determined to be present, matching control parameters can be determined based on the smoke feature data; then, the smoke extraction equipment can be automatically controlled to accurately remove the current smoke based on the control parameters, thereby achieving a better smoke extraction effect.

[0121] This specification also provides a computer device, including a processor and a memory for storing processor-executable instructions. Specifically, the processor can perform the following steps according to the instructions: acquiring association information of a target surgical instrument and association information of a target organ to be operated on; determining matching first control parameters based on the association information of the target surgical instrument and the association information of the target organ; and activating and controlling a smoke extraction device to be in standby mode according to the first control parameters, so as to perform smoke removal processing when smoke is detected during the operation.

[0122] To execute the above instructions more accurately, please refer to... Figure 9 As shown in the embodiments of this specification, another specific computer device is also provided, wherein the computer device includes a network communication port 901, a processor 902, and a memory 903. The above structures are connected by internal cables so that the various structures can perform specific data interaction.

[0123] Specifically, the network communication port 901 can be used to obtain the association information of the target surgical instruments and the association information of the target organ to be operated on.

[0124] The processor 902 can be specifically used to determine a matching first control parameter based on the association information of the target surgical instrument and the association information of the target organ; and to start and control the smoke exhaust device to be in standby mode according to the first control parameter so as to perform smoke removal processing when smoke is detected during the operation.

[0125] The memory 903 can be used to store the corresponding instruction program.

[0126] In this embodiment, the network communication port 901 can be a virtual port bound to different communication protocols, thereby enabling the sending or receiving of different data. For example, the network communication port can be a port responsible for web data communication, a port responsible for FTP data communication, or a port responsible for email data communication. Furthermore, the network communication port can also be a physical communication interface or communication chip. For example, it can be a wireless mobile network communication chip, such as GSM or CDMA; it can also be a Wi-Fi chip; or it can be a Bluetooth chip.

[0127] In this embodiment, the processor 902 can be implemented in any suitable manner. For example, the processor can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers, etc. This specification is not limiting.

[0128] In this embodiment, the memory 903 may include multiple layers. In a digital system, anything that can store binary data can be a memory. In an integrated circuit, a circuit with storage function but no physical form is also called a memory, such as RAM, FIFO, etc. In a system, a storage device with a physical form is also called a memory, such as a memory stick, TF card, etc.

[0129] This specification also provides another computer device, including a processor and a memory for storing processor-executable instructions. Specifically, the processor can perform the following steps according to the instructions: acquiring surgical images during the surgical procedure; acquiring effective image features based on the surgical images; wherein the effective image features include at least two of the following: grayscale value, mode grayscale value, median grayscale value, average grayscale value, grayscale value variance, area ratio, perimeter ratio, and grayscale value distribution ratio; and controlling a smoke extraction device to perform corresponding smoke removal processing during the surgical procedure based on the effective image features.

[0130] This specification also provides a computer storage medium based on the above-described surgical smoke processing method. The computer storage medium stores computer program instructions, which, when executed, perform the following: acquiring the association information of the target surgical instrument and the association information of the target organ to be operated on; determining matching first control parameters based on the association information of the target surgical instrument and the association information of the target organ; and activating and controlling the smoke extraction device to be in standby mode based on the first control parameters, so as to perform smoke removal processing when smoke is detected during the operation.

[0131] This specification also provides another computer storage medium based on the above-described method for processing surgical smoke. The computer storage medium stores computer program instructions that, when executed, perform the following: acquiring surgical images during the surgical procedure; acquiring effective image features based on the surgical images; wherein the effective image features include at least two of the following: grayscale value, mode grayscale value, median grayscale value, average grayscale value, grayscale value variance, area ratio, perimeter ratio, and grayscale value distribution ratio; and controlling the smoke extraction device to perform corresponding smoke removal processing during the surgical procedure based on the effective image features.

[0132] In this embodiment, the storage medium includes, but is not limited to, Random Access Memory (RAM), Read-Only Memory (ROM), cache, hard disk drive (HDD), or memory card. The memory can be used to store computer program instructions. The network communication unit can be an interface configured according to standards specified in the communication protocol for network connection communication.

[0133] In this embodiment, the specific functions and effects implemented by the program instructions stored in the computer storage medium can be explained in comparison with other implementation methods, and will not be repeated here.

[0134] See Figure 10 As shown in the specification, this specification also provides a medical system, which may specifically include: a surgical smoke treatment device, an endoscope, a chip reading unit, and a smoke extraction device, wherein the chip reading unit is used to acquire the association information of the target surgical instruments, the endoscope is used to acquire the association information of the target organ to be operated on, and the surgical smoke treatment device is used to remove the smoke during the operation by controlling the smoke extraction device according to the association information of the target surgical instruments and the association information of the target organ.

[0135] See Figure 11 As shown, at the software level, this specification also provides a surgical smoke processing device, which may specifically include the following structural modules:

[0136] The acquisition module 1101 can be used to acquire the association information of the target surgical instrument and the association information of the target organ to be operated on.

[0137] The determination module 1102 can be used to determine the matching first control parameters based on the association information of the target surgical instrument and the association information of the target organ.

[0138] The processing module 1103 can be used to start and control the smoke exhaust equipment to be in standby mode according to the first control parameters, so as to perform smoke removal when smoke is detected during the operation.

[0139] In some embodiments, after the device starts and controls the smoke exhaust equipment to be in standby mode according to the first control parameter, it can also be used to acquire surgical images during the operation through the acquisition module 1101; determine smoke feature data based on the surgical images through the determination module 1102; and control the smoke exhaust equipment to perform corresponding smoke removal processing through the processing module 1103 based on the smoke feature data and the first control parameter.

[0140] In some embodiments, when the processing module 1103 is specifically implemented, it can determine smoke feature data based on the surgical image in the following manner: obtain effective image features based on the surgical image; wherein, the effective image features include at least one of the following: gray value of the image, mode gray value, median gray value, average gray value, gray value variance, area ratio, perimeter ratio, gray value distribution ratio; determine smoke feature data based on the effective image features.

[0141] In some embodiments, when the above-mentioned processing module 1103 is specifically implemented, it can control the smoke exhaust device to perform corresponding smoke removal processing according to the smoke characteristic data and the first control parameter in the following manner: determine whether smoke exists according to the smoke characteristic data; if smoke is determined to exist, control the smoke exhaust device to perform corresponding smoke removal processing according to the smoke characteristic data and the first control parameter.

[0142] In some embodiments, when the processing module 1103 is specifically implemented, it can control the smoke exhaust device to perform corresponding smoke removal processing according to the smoke characteristic data and the first control parameter in the following manner: determining a matching second control parameter according to the smoke characteristic data; detecting whether the second control parameter meets a preset parameter threshold range; wherein, the preset parameter threshold range is determined according to the first control parameter; if it is determined that the second control parameter meets the preset parameter threshold range, controlling the smoke exhaust device to perform corresponding smoke removal processing according to the first control parameter.

[0143] In some embodiments, when the processing module 1103 is specifically implemented, it can determine the matching second control parameter based on the smoke feature data in the following manner: process the smoke feature data using a preset smoke matching model to obtain the second control parameter.

[0144] In some embodiments, after detecting whether the second control parameter meets the preset parameter threshold range, the above-mentioned processing module 1103 can also be used to control the smoke exhaust device to perform corresponding smoke removal processing according to the second control parameter when it is determined that the second control parameter does not meet the preset parameter threshold range.

[0145] In some embodiments, when the processing module 1103 is specifically implemented, it can control the smoke exhaust device to perform corresponding smoke removal processing according to the second control parameters in the following manner: according to the second control parameters, a corresponding control instruction is encapsulated; the control instruction is sent to the smoke exhaust unit; wherein, the smoke exhaust unit is connected to the smoke exhaust device; the smoke exhaust unit is used to verify the control instruction; if the verification is successful, the smoke exhaust unit controls the smoke exhaust device to perform smoke exhaust operation according to the control instruction.

[0146] In some embodiments, the associated information of the target surgical instrument includes at least one of the following: the instrument type of the target surgical instrument, the electrosurgical energy level of the target surgical instrument, the lifespan information of the target surgical instrument, etc.

[0147] In some embodiments, when the acquisition module 1101 is specifically implemented, it can acquire the associated information of the target surgical instrument in the following manner: read the chip information of the storage chip of the target surgical instrument; and acquire the associated information of the target surgical instrument based on the chip information.

[0148] In some embodiments, the associated information of the target organ may specifically include: the organ type and / or lesion information of the target organ, etc.

[0149] In some embodiments, when the acquisition module 1101 is specifically implemented, it can acquire the associated information of the target organ in the following manner: acquiring an organ image of the target organ to be operated on; performing image recognition on the organ image to obtain the associated information of the target organ.

[0150] In some embodiments, when the determination module 1102 is specifically implemented, it can determine the matching first control parameter according to the association information of the target surgical instrument and the association information of the target organ in the following manner: combine the association information of the target surgical instrument and the association information of the target organ to obtain target combination data; use a preset smoke prediction model to process the target combination data to obtain the corresponding prediction result; and determine the matching first control parameter according to the prediction result.

[0151] In some embodiments, the preset smoke prediction model may be specifically constructed in advance by training the model using historical surgical fogging records.

[0152] This manual also provides another surgical fume treatment device, which may include the following structural modules:

[0153] The first acquisition module can be used to acquire surgical images during the surgical process;

[0154] The second acquisition module can be used to acquire effective image features based on the surgical image; wherein, the effective image features include at least two of the following: gray value, mode gray value, median gray value, average gray value, gray value variance, area ratio, perimeter ratio, and gray value distribution ratio of the image;

[0155] The processing module can be used to control the smoke extraction device to perform corresponding smoke removal processing during the operation based on the effective image features.

[0156] It should be noted that the units, devices, or modules described in the above embodiments can be implemented by computer chips or physical entities, or by products with certain functions. For ease of description, the above devices are described by dividing them into various modules according to their functions. Of course, in implementing this specification, the functions of each module can be implemented in one or more software and / or hardware, or the module that implements the same function can be implemented by a combination of multiple sub-modules or sub-units, etc. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection between the devices or units shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0157] As can be seen from the above, the surgical smoke treatment device provided in the embodiments of this specification can, before surgery, first acquire the association information of the target surgical instruments to be used and the association information of the target organs to be operated on; then, based on the association information of the target surgical instruments and the target organs, determine the matching first control parameters; and then, based on the first control parameters, start and control the smoke extraction device to be in standby mode in advance. During surgery, smoke characteristic data can be determined by collecting and analyzing surgical images during the surgery in real time or at regular intervals; then, based on the smoke characteristic data and the first control parameters, control the smoke extraction device to perform smoke removal. This enables intelligent and accurate identification and automatic removal of smoke generated during surgery, effectively reducing the interference of smoke on the surgical field of vision and reducing surgical risks. Furthermore, by using a preset smoke prediction model to process the association information of the target surgical instruments and the target organs, it is possible to predict in advance whether smoke may be generated during the surgery to be performed, as well as the possible concentration and range of smoke, and thus accurately determine the appropriate first control parameters to pre-control the smoke extraction power of the smoke extraction device. Furthermore, by acquiring surgical images during the operation and extracting multiple effective image features from these images, and then, based on statistical principles and by integrating these multiple effective image features through multi-dimensional analysis, a suitable second control parameter is accurately determined, allowing for timely and flexible adjustment of the current smoke extraction power of the smoke extraction equipment. This results in a relatively better smoke extraction effect.

[0158] While this specification provides the steps of operation for the methods described in the embodiments or flowcharts, more or fewer steps may be included based on conventional or non-inventive means. The order of steps listed in the embodiments is merely one possible order of execution among many steps and does not represent the only possible order. In actual device or client product execution, the methods shown in the embodiments or drawings may be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment, or even a distributed data processing environment). The terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, product, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, product, or apparatus. Without further limitations, the presence of other identical or equivalent elements in a process, method, product, or apparatus that includes said elements is not excluded. The terms "first," "second," etc., are used to denote names and do not indicate any particular order.

[0159] Those skilled in the art will also know that, besides implementing the controller using purely computer-readable program code, the same functions can be achieved by logically programming the method steps, making the controller function as logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers (PLCs), and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the devices within it used to implement various functions can also be considered structures within that hardware component. Alternatively, the devices used to implement various functions can be considered as both software modules implementing the method and structures within a hardware component.

[0160] This specification can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, classes, etc., that perform a specific task or implement a specific abstract data type. This specification can also be practiced in distributed computing environments, where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0161] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this specification can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions of this specification can essentially be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, mobile terminal, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments of this specification.

[0162] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. This specification can be used in numerous general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable electronic devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices, etc.

[0163] Although this specification has been described by way of examples, those skilled in the art will recognize that many variations and modifications are possible without departing from the spirit of this specification, and it is intended that the appended claims cover such variations and modifications without departing from the spirit of this specification.

Claims

1. A method for treating surgical fumes, characterized in that, include: Obtain the associated information of the target surgical instruments, the target surgical environment, and the associated information of the target organ to be operated on; Based on the association information of the target surgical instruments and the target organs, combined with the target surgical environment information, the potential future smoke conditions are predicted in advance. Furthermore, based on the mapping relationship between the smoke conditions and the smoke extraction power and control parameters of the smoke extraction equipment for different smoke conditions, a first control parameter for that smoke condition is determined in advance. The first control parameter includes one or more of the following: smoke extraction power, smoke extraction direction, and smoke extraction airflow. The target surgical environment information includes one or more of the following: surgical type, temperature, and humidity. The association information of the target surgical instruments includes at least the lifespan information of the target surgical instruments. Based on the first control parameter, the smoke extraction equipment is started and controlled to be in standby mode so that smoke can be removed when smoke is detected during the operation.

2. The method according to claim 1, characterized in that, The associated information of the target surgical instrument also includes at least one of the following: the instrument type of the target surgical instrument, and the electrosurgical energy level of the target surgical instrument.

3. The method according to claim 2, characterized in that, Obtain the associated information of the target surgical instrument, including: Read the chip information of the target surgical instrument's storage chip; Based on the chip information, obtain the associated information of the target surgical instrument.

4. The method according to claim 1, characterized in that, The associated information for the target organ includes: the organ type and / or lesion information of the target organ.

5. The method according to claim 4, characterized in that, Obtain the association information of the target organ, including: Acquire organ images of the target organ to be operated on; Image recognition is performed on the organ image to obtain the associated information of the target organ.

6. The method according to claim 1, characterized in that, Based on the association information of the target surgical instrument and the target organ, the matching first control parameters are determined, including: By combining the association information of the target surgical instruments and the association information of the target organs, target combination data is obtained; By processing target combination data using a pre-defined smoke prediction model, the corresponding prediction results are obtained. Based on the prediction results, determine the first matching control parameter.

7. A medical system, characterized in that, include: The surgical smoke treatment device, endoscope, chip reading unit, and smoke extraction device are provided, wherein the chip reading unit is used to acquire the association information of the target surgical instruments, the endoscope is used to acquire the association information of the target organ to be operated on, and the surgical smoke treatment device is used to control the smoke extraction device to remove smoke during the operation based on the association information of the target surgical instruments and the association information of the target organ, using the surgical smoke treatment method of any one of claims 1 to 6.

8. A computer device, characterized in that, It includes a processor and a memory for storing processor-executable instructions, wherein the processor, when executing the instructions, implements the relevant steps of the surgical smoke treatment method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, It stores computer instructions that, when executed, implement the relevant steps of the method according to any one of claims 1 to 6.

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