Hysteroscopic surgery bleeding amount monitoring method

Abstract

The invention relates to the technical field of bleeding amount monitoring, in particular to a hysteroscopic surgery bleeding amount monitoring method, which comprises the following steps of: performing preprocessing and feature extraction on an acquired hysteroscopic image, and determining a bleeding point location and a bleeding area; establishing a bleeding model, and dynamically calculating a first value of the bleeding amount according to the bleeding point location and the bleeding area data; a multispectral sensor is arranged in the suction pipeline, liquid components are analyzed in real time through multiple wavelengths, and the hemoglobin concentration is calculated; determining a second value of the amount of bleeding based on the fluid flow rate within the aspiration conduit; collecting heart rate and blood pressure data of a patient, performing data fusion in combination with the first value and the second value of the bleeding amount, dynamically adjusting the weight, and outputting an estimated value of the bleeding amount; setting graded early warning thresholds, and executing prompts of corresponding grades when the thresholds are reached; according to the invention, dynamic weight adjustment is carried out on the first value and the second value; and combining the first value and the second value with the dynamic weight, fusing and outputting a bleeding amount prediction value so as to improve the prediction accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of bleeding volume monitoring, and more particularly to a method for monitoring bleeding volume during hysteroscopic surgery. Background Art

[0002] Hysteroscopy is a new, minimally invasive gynecological diagnostic and treatment technology. It is a fiber-light endoscope used for intrauterine examination and treatment. It includes a hysteroscope, an energy system, a light source system, a perfusion system, and an imaging system. It uses the front of the scope to enter the uterine cavity, which has a magnifying effect on the observed area. It is the preferred examination method for gynecological bleeding diseases and intrauterine lesions because of its intuitive and accurate nature. Hysteroscopy can not only determine the location, size, appearance, and scope of the lesion, but also conduct detailed observation of the tissue structure on the surface of the lesion, and directly obtain samples or perform positioning curettage. This greatly improves the accuracy of the diagnosis of intrauterine diseases, and updates, develops, and compensates for the shortcomings of traditional diagnostic and treatment methods. For most patients who are suitable for diagnostic curettage, it is more reasonable and effective to first perform a hysteroscopy to determine the location of the lesion and then perform a biopsy or curettage. It can accurately measure the volume of the uterine cavity and whether the fallopian tubes are unobstructed, and conduct effective interventional examinations and treatments for infertility caused by small uterus, immature uterus, uterine cavity adhesions, fallopian tube obstruction, etc. It can quickly unclog the fallopian tubes and eliminate the causes of female infertility. It is an advanced infertility examination and treatment instrument.

[0003] Hysteroscopic surgery, due to its minimally invasive nature and rapid recovery, has been widely used in the uterine cavity. It is primarily used to treat various uterine conditions, including abnormal uterine bleeding, intrauterine adhesions, submucosal uterine fibroids, and scar pregnancy. During surgery, the surgeon typically uses distending fluid to dilate the uterine cavity and distend the uterus through a perfusion system. The distending fluid that flows out of the uterus is collected in a container. During surgery, tissue cutting, uterine perforation, vascular injury, and improper handling can all cause bleeding. Therefore, monitoring the patient's bleeding volume is necessary to assess the patient's condition and mitigate surgical risks. Conventional methods involve direct observation of bleeding within the hysteroscope or empirical analysis based on the color of the distending fluid mixed with blood and the patient's blood pressure. However, relying solely on empirical analysis can be sluggish, and the dilution effect of the distending fluid on the blood makes it difficult to accurately estimate bleeding volume.

[0004] Therefore, how to accurately estimate the amount of bleeding during surgery has become a technical problem that needs to be solved urgently. Summary of the Invention

[0005] In order to solve the above technical problems, the present invention provides a method for monitoring bleeding volume during hysteroscopic surgery.

[0006] According to one aspect of the present invention, a method for monitoring bleeding volume during hysteroscopic surgery is provided, comprising the following steps:

[0007] S1: Preprocessing and feature extraction of collected hysteroscopic images to determine bleeding points and bleeding areas;

[0008] S2: Establish a bleeding model and dynamically calculate the first value of bleeding volume based on the bleeding point and bleeding area data;

[0009] S3: A multispectral sensor is installed in the suction pipe to analyze the liquid composition in real time using multiple wavelengths to calculate the hemoglobin concentration;

[0010] S4: determining a second value of the bleeding volume based on the liquid flow rate in the suction tube;

[0011] S5: Collect the patient's heart rate and blood pressure data, combine the first and second values of the bleeding volume to perform data fusion, dynamically adjust the weight, and output the estimated value of the bleeding volume;

[0012] S6: Set the graded warning threshold and execute the corresponding level of prompt when the threshold is reached.

[0013] Preferably, in step S1, the image collected in real time is preprocessed, and then feature extraction is performed; the preprocessed RGB image is converted into HSV space, and the bleeding area is segmented using blood color features.

[0014] Preferably, the bleeding area is calculated based on the pixel area of the bleeding region accounting for the total pixel area of the hysteroscopic image and the viewing area area of the hysteroscopic image.

[0015] Preferably, in step S2, three bleeding models are established: traumatic bleeding, perforation bleeding, and vascular injury bleeding; based on actual detection data, the bleeding type is determined, and the first value of the bleeding volume is calculated using the corresponding bleeding model.

[0016] Preferably, in step S3, the concentration of hemoglobin is calculated based on the concentration detection according to the Beer-Lambert law using a dual-wavelength compensation algorithm at 540 nm and 570 nm.

[0017] Preferably, in step S4, an integral calculation is performed based on the calculated hemoglobin concentration data in combination with the real-time flow rate to obtain a second value of the bleeding volume.

[0018] Preferably, in step S5, weights are set for the first value and the second value data respectively, and the weights are dynamically adjusted according to the confidence level; and the first value and the second value are weighted and summed to calculate the estimated bleeding volume.

[0019] Preferably, thresholds are set based on clinical data and divided into several levels; each level is set with corresponding warnings and corresponding operating procedures;

[0020] The warning level is determined based on the calculated estimated bleeding volume and the corresponding warning and operating procedures are executed.

[0021] A second aspect of the present invention provides a hysteroscopic surgery bleeding volume monitoring system, comprising a data acquisition module, a data calculation module, a data output module and a communication module;

[0022] In this embodiment, the data acquisition module includes an image acquisition unit, a multispectral acquisition unit, and a monitoring unit;

[0023] The image acquisition unit is used to acquire image data of the hysteroscope to facilitate subsequent analysis and processing to obtain the first value;

[0024] The multi-spectral acquisition unit is arranged in the suction tube to measure the liquid flowing through the suction tube and calculate the second value of the bleeding volume through the hemoglobin concentration and flow rate;

[0025] The data calculation module is used to process and calculate the data collected by the data acquisition unit and obtain the calculation results;

[0026] The data output module is used to output the calculation results;

[0027] The communication module is used for the system to communicate with various sensors and real-world devices, and to display calculation results in real time to help doctors quickly determine the amount of bleeding during surgery.

[0028] The third aspect of the present invention provides a computer program, which includes computer instructions, which are stored in a computer-readable storage medium; the processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the steps of the above-mentioned hysteroscopic surgery bleeding volume monitoring method.

[0029] A fourth aspect of the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and wherein the processor implements the steps of the above-mentioned method for monitoring bleeding volume during hysteroscopic surgery when executing the computer program.

[0030] Compared with the existing technology, the present invention processes the image data collected by the hysteroscope to quickly obtain the first value of the bleeding volume; improves the corresponding speed; and simultaneously uses the distending fluid mixed with blood in the suction tube to measure and determine the hemoglobin concentration, and then determines the second value of the bleeding volume; the first value can be verified by the delayed second value; at the same time, a deviation threshold is set and compensated; by introducing confidence, the first value and the second value are dynamically weighted and adjusted; the first value and the second value are combined with the dynamic weight fusion to output the bleeding volume prediction value to improve the accuracy of the prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0032] Figure 1 Flowchart of a method for monitoring bleeding volume during hysteroscopic surgery according to an embodiment of the present invention.

[0033] Figure 2 4 is a block diagram of a system for monitoring bleeding volume during hysteroscopic surgery according to an embodiment of the present invention.

[0034] Figure 3 A schematic structural diagram of a computer system suitable for implementing an electronic device according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0035] Below, the exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described herein.

[0036] As discussed in the background art above, conventional methods rely on doctors directly observing bleeding within the hysteroscope, or on empirical analysis based on the color of the distending fluid mixed with blood and the patient's blood pressure, to estimate bleeding volume. This solution addresses the problem that relying solely on empirical analysis can lead to a certain degree of hysteresis, and the dilution effect of the distending fluid on the blood makes it difficult to accurately estimate bleeding volume immediately.

[0037] Example 1

[0038] like Figure 1 As shown, this embodiment provides a method for monitoring bleeding volume during hysteroscopic surgery, comprising the following specific steps:

[0039] S1: Preprocessing and feature extraction of the collected hysteroscopic image to determine the bleeding point and bleeding area; In step S1, the real-time collected image is preprocessed and then feature extraction is performed; the preprocessed RGB image is converted into HSV space, and the bleeding area is segmented using the blood color feature; Since the bleeding area has a significant color difference compared to normal human tissue, the bleeding area is segmented by setting the blood color feature based on the collected hysteroscopic image;

[0040] The bleeding area is then calculated based on the pixel area of the bleeding area to the total pixel area of the hysteroscopic image and the viewing area of the hysteroscopic image. The bleeding area is calculated using the following formula:

[0041]

[0042] In the above formula, A img Bleeding area (cm 2 ) Nq is the bleeding pixel, Nz is the visual area pixel; As is the actual area of the hysteroscope visual area, which is related to the magnification of the hysteroscope. For example, when the number of pixels in the bleeding area detected is 1200 and the total number of pixels is 50,000, the actual area is 4.8 cm 2 , then according to the above calculation, we can know the bleeding area A img 0.1152cm 2 .

[0043] S2: Establish a bleeding model and dynamically calculate the first value of the bleeding volume based on the bleeding point and bleeding area data; in step S2, three bleeding models are established: trauma bleeding, perforation bleeding, and vascular injury bleeding; based on the actual detection data, the bleeding type is determined, and the first value of the bleeding volume is calculated using the corresponding bleeding model.

[0044] In this embodiment, three different bleeding models were established based on clinical or simulation experiments, corresponding to the three most common bleeding models in actual surgery: traumatic bleeding, perforation bleeding, and vascular injury bleeding. The traumatic bleeding model primarily describes bleeding after surgical resection of human tissue. The bleeding rate is typically low, typically less than 1.5 ml / min, and is characterized by slow exudation. The image typically appears as a diffuse patch with blurred edges and no clear ejection point. The bleeding rate is weakly correlated with changes in uterine intracavitary pressure. The perforation bleeding model generally addresses high-risk bleeding. During cervical dilation or hysteroscopic insertion, improper manipulation, such as excessive force or incorrect direction, can cause the instrument to penetrate the uterine wall, causing perforation and further bleeding. In perforation bleeding, the bleeding rate is relatively fast, typically exceeding 5 ml / min, with deformation of the uterine cavity contour and the presence of bubbles or tissue fragments. The bleeding rate surges with a sudden drop in uterine intracavitary pressure. The vascular injury bleeding model, on the other hand, has a moderate bleeding rate, typically between 1.5 and 5 ml, with a point-like ejection and a dynamic blood column.

[0045] Traumatic bleeding model:

[0046] Q 创伤 =k1·A(t)·t+C 基线

[0047] In the above formula, k1 is the bleeding rate coefficient, which needs to be calibrated through experiments; A(t) is the real-time bleeding area (cm 2), C baseline is the amount of blood seepage before operation.

[0048] Perforation bleeding model:

[0049] Q 穿孔 =Q0·e t / τ +αΔP drop

[0050] In the above formula, Q0 is the initial bleeding rate (ml / min), τ is the time constant used to characterize the bleeding acceleration trend; α is the pressure sensitivity coefficient; ΔP drop is the decrease in intrauterine pressure (mmHg).

[0051] Vascular injury bleeding model:

[0052]

[0053] In the above formula, r is the vascular radius (mm), ΔP(t) is the pressure difference between the bleeding point and the uterine cavity; η is the blood viscosity; L is the length of the vascular injury, which is generally 2 mm.

[0054] In this model, it is necessary to analyze the blood column expansion distance in combination with continuous frame images to determine the instantaneous flow velocity, thereby more accurately calculating the bleeding volume.

[0055]

[0056] ΔP(t)=k2·v 2

[0057] In the above formula, b is the pixel calibration coefficient; k² is the fitting constant, which requires calibration through experimentation. In this step, the appropriate model can be selected based on the collected bleeding point, bleeding area, and bleeding type to improve the accuracy of bleeding volume calculation.

[0058] Specifically, for example, when the bleeding point and bleeding area in the collected image are very small, it can be determined to be traumatic bleeding, and the traumatic bleeding model can be called for calculation; if an injection point appears in the image, it is vascular damage, and the vascular damage bleeding model is called for calculation; if the uterine cavity pressure drops significantly, exceeds the threshold, and no injection point appears, it is considered to be perforation bleeding, and the perforation bleeding model is called for calculation.

[0059] S3: A multispectral sensor is set in the suction pipe to analyze the liquid components in real time through multi-wavelength analysis and calculate the hemoglobin concentration. In step S3, the concentration is detected based on the Beer-Lambert law and the hemoglobin concentration is calculated using a dual-wavelength compensation algorithm of 540nm and 570nm.

[0060] The calculation formula is as follows:

[0061]

[0062] In the above formula, I0 λ is the incident light intensity; I λ is the transmitted light intensity; ε Hb is the molar absorption coefficient of hemoglobin; F is the optical path length.

[0063] S4: Determine a second value of the bleeding volume based on the liquid flow rate in the suction tube. In step S4, an integral calculation is performed based on the calculated hemoglobin concentration data and the real-time flow rate to obtain the second value of the bleeding volume. The calculation formula is as follows:

[0064]

[0065] In the above formula, the denominator 150 is the normal blood hemoglobin concentration (g / l); Q2 is the amount of bleeding; t0 is the initial time, t is the current time; f(τ) is the real-time flow rate; C Hb (τ) is the real-time hemoglobin concentration;

[0066] In this step, in order to reduce the measurement error, it is necessary to inject uterine distension fluid into the patient's uterus, and when the uterine cavity is fully expanded and reaches the appropriate pressure value, the surgical operation and measurement are performed; during hysteroscopic surgery, the uterine distension fluid flows out from an outlet of the hysteroscope, part of which flows out from the gap between the hysteroscope and the cervix, and part of which enters the abdominal cavity and is absorbed by the blood vessels; therefore, during the operation, when the injection volume and outflow volume reach a steady state, the measurement is performed, and the data is more accurate; at this time, the method of step S4 is used to calculate the bleeding volume in the suction tube, and the C in the trauma bleeding model in step S2 can be obtained. 基线 The value of; during the operation, the amount of bleeding during the operation is calculated, that is, the second value.

[0067] S5: Collect the patient's heart rate and blood pressure data, combine the first value and the second value of the bleeding volume for data fusion, dynamically adjust the weight, and output the estimated bleeding volume; in step S5, set weights for the first value and the second value data respectively, and dynamically adjust the weights according to the confidence level; perform weighted summation on the first value and the second value to calculate the estimated bleeding volume.

[0068] In this embodiment, intraoperative monitoring of the patient's heart rate and blood pressure assists in determining the presence of massive bleeding, determining the confidence level of the first and second values, and adaptively adjusting their corresponding weights. For example, in traumatic and vascular injury bleeding models, blood pressure changes slightly, while heart rate increases slightly. In contrast, in perforation bleeding models, blood pressure decreases rapidly, while heart rate increases significantly. Therefore, combining basic intraoperative information such as blood pressure and heart rate can assist in determining the patient's bleeding status. Furthermore, based on experience and experimental data analysis, a deviation threshold is set for the first and second values. When there is a significant deviation between the first and second values, the weight of the value with higher confidence is increased, while the threshold of the value with lower confidence is decreased. Because the first value is calculated directly through hysteroscopic observation, while the second value is calculated based on the amount of bleeding by calculating the outflow of uterine distention fluid, the second value has a significant lag compared to the first value. Therefore, the second value data needs to be corrected to compensate for the lag in the detection results. The correction coefficient is obtained using simulation models or experimental data. During the experimental data collection process, the recovered amount of distension fluid minus the injected amount, and then the distension fluid absorbed by the blood vessels and the human tissue after clearance can be deducted to determine the accurate amount of bleeding; the bleeding volume data obtained from the actual experiment is compared with the first value and the second value to dynamically adjust the weight and output a more accurate calculation to improve the accuracy of the model.

[0069] In this embodiment, the first value is defined as Q1, and the variance is σ1 2 ; The second value is Q2, and the variance is σ2 2 The sum of the weight w1 of the first value and the weight w2 of the second value is 1; the fusion result Q d =w1Q1+w2Q2.

[0070] Choose the inverse of the variance as the confidence level:

[0071]

[0072] The initial weights are divided into W2=1-W1.

[0073] Deviation threshold Where D is the adjustment coefficient, which can be adjusted manually and has a default value of 2. When the absolute value of the difference between Q1 and Q2 is greater than the deviation threshold ΔQ, the weight correction is triggered.

[0074] The revised rules are as follows:

[0075] If σ1 2 <σ2 2 , then adjust W1 to: W1 new =min(W1+δ,0.9),W2 new =1-W1 new

[0076] If σ1 2 ≥σ2 2 , then adjust W2 to: W2 new =min(W2+δ,0.9),W1 new =1-W2 new

[0077] In the above formula, δ is the weight increase step size.

[0078] S6: Set the graded warning thresholds and execute the corresponding level of prompts when the thresholds are reached. Set the thresholds based on clinical data and divide them into several levels; set the corresponding warnings and corresponding operating procedures for each level;

[0079] The warning level is determined based on the calculated estimated bleeding volume and the corresponding warning and operating procedures are executed.

[0080] For example, electrocoagulation forceps are used for traumatic bleeding, and hemostatic drugs are applied locally; 4°C cold saline is continuously infused to use low temperature to constrict blood vessels and reduce bleeding; at the same time, attention is paid to postoperative bleeding.

[0081] In case of perforation bleeding, the laparoscope should be withdrawn immediately and the infusion of uterine distension fluid should be stopped; two intravenous channels should be established and crystalloid fluid should be infused; interventional embolization and balloon compression should be used to stop bleeding.

[0082] Use bipolar electrocoagulation for hemostasis of vascular injuries, and use hemostatic clips or sutures for hemostasis; use vasoconstrictors at the same time; and pay attention to postoperative bleeding.

[0083] Example 2

[0084] like Figure 2 As shown, this embodiment provides a hysteroscopic surgery bleeding volume monitoring system, including a data acquisition module, a data calculation module, a data output module and a communication module;

[0085] In this embodiment, the data acquisition module includes an image acquisition unit, a multispectral acquisition unit, and a monitoring unit;

[0086] The image acquisition unit is used to acquire image data of the hysteroscope to facilitate subsequent analysis and processing to obtain the first value;

[0087] The multi-spectral acquisition unit is arranged in the suction tube to measure the liquid flowing through the suction tube and calculate the second value of the bleeding volume through the hemoglobin concentration and flow rate;

[0088] The data calculation module is used to process and calculate the data collected by the data acquisition unit and obtain the calculation results;

[0089] The data output module is used to output the calculation results;

[0090] The communication module is used for the system to communicate with various sensors and real-world devices, and to display calculation results in real time to help doctors quickly determine the amount of bleeding during surgery.

[0091] Example 3

[0092] Figure 3 A schematic structural diagram of a computer system suitable for implementing an electronic device according to an embodiment of the present invention is shown.

[0093] It should be noted that the computer system of the electronic device in this embodiment is only an example and should not bring any limitation to the functions and scope of use of the embodiment of the present invention.

[0094] In this embodiment, the computer system includes a central processing unit (CPU) 401, which can execute various appropriate actions and processes based on programs stored in a read-only memory (ROM) 402 or programs loaded from a storage unit 408 into a random access memory (RAM) 403, such as executing the method for monitoring hysteroscopic bleeding volume described in the above-mentioned embodiment. The RAM 403 also stores various programs and data required for system operation. The CPU 401, ROM 402, and RAM 403 are interconnected via a bus 404. An input / output interface 405 is also connected to the bus 404.

[0095] The following components are connected to the input / output interface 405: an input section 406 including a keyboard, a mouse, and the like; an output section 407 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 408 including a hard disk and the like; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the input / output interface 405 as needed. Removable media 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like, is installed in the drive 410 as needed so that computer programs read therefrom can be installed into the storage section 408 as needed.

[0096] In particular, according to an embodiment of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, an embodiment of the present invention includes a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 409 and / or installed from a removable medium 411. When the computer program is executed by the central processing unit 401, the various functions defined in the system of the present invention are performed.

[0097] It should be noted that the computer-readable medium shown in the embodiments of the present invention may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. 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 thereof. 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), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a 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 the present invention, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable computer program. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. 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 connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0098] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the boxes can also occur in an order different from that marked in the accompanying drawings. For example, two boxes shown 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 or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or can be implemented using a combination of dedicated hardware and computer instructions.

[0099] The units involved in the embodiments of the present invention may be implemented in software or hardware, and the units described may also be provided in a processor. In some cases, the names of these units do not limit the units themselves.

[0100] According to one aspect of the present invention, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in the various optional implementations described above.

[0101] As another aspect, the present invention further provides a computer-readable medium, which may be included in the electronic device described in the above embodiments, or may exist independently and not be incorporated into the electronic device. The computer-readable medium carries one or more programs, and when executed by the electronic device, the electronic device implements the method for monitoring hysteroscopic surgical bleeding volume described in the above embodiments.

[0102] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more modules or units described above can be concretized in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units to be concretized.

[0103] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes a number of instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present invention.

[0104] Here, those skilled in the art will appreciate that the specific operations of each step in the above-mentioned hysteroscopic surgery bleeding volume monitoring method have been described in detail in the reference to Figures 1 to 2 The description of the method for monitoring bleeding volume during hysteroscopic surgery has been described in detail, and therefore, its repeated description will be omitted.

[0105] In summary, a method for monitoring bleeding volume during hysteroscopic surgery based on an embodiment of the present invention is explained, which processes image data collected by the hysteroscope to quickly obtain a first value of the bleeding volume; improves the corresponding speed; and simultaneously uses the distending fluid mixed with blood in the suction tube for measurement to determine the hemoglobin concentration, and then determines the second value of the bleeding volume; the first value can be verified by the delayed second value; at the same time, a deviation threshold is set and compensated; by introducing confidence, the first value and the second value are dynamically weighted; the first value and the second value are combined with the dynamic weight fusion to output a predicted value of bleeding volume to improve the accuracy of the prediction.

Claims

1. A method for monitoring bleeding volume during hysteroscopic surgery, characterized in that: The following steps are involved: S1: Preprocessing and feature extraction of collected hysteroscopic images to determine bleeding points and bleeding areas; S2: Establish a bleeding model and dynamically calculate the first value of bleeding volume based on the bleeding point and bleeding area data; S3: A multispectral sensor is installed in the suction pipe to analyze the liquid composition in real time using multiple wavelengths to calculate the hemoglobin concentration; S4: determining a second value of the bleeding volume based on the liquid flow rate in the suction tube; S5: Collect the patient's heart rate and blood pressure data, combine the first and second values of the bleeding volume to perform data fusion, dynamically adjust the weight, and output the estimated value of the bleeding volume; S6: Set the graded warning threshold and execute the corresponding level of prompt when the threshold is reached.

2. The method for monitoring bleeding volume during hysteroscopic surgery according to claim 1, wherein: In step S1, the image collected in real time is preprocessed, and then feature extraction is performed; the preprocessed RGB image is converted into HSV space, and the bleeding area is segmented using blood color features.

3. The method for monitoring bleeding volume during hysteroscopic surgery according to claim 2, wherein: In step S1 , the bleeding area is calculated based on the pixel area of the bleeding area accounting for the total pixel area of the hysteroscopic image and the viewing area area of the hysteroscopic image.

4. The method for monitoring bleeding volume during hysteroscopic surgery according to claim 1, wherein: In step S2, three bleeding models are established: traumatic bleeding, perforation bleeding, and vascular injury bleeding; based on actual detection data, the bleeding type is determined, and the first value of the bleeding volume is calculated using the corresponding bleeding model.

5. The method for monitoring bleeding volume during hysteroscopic surgery according to claim 1, wherein: In step S3, the concentration of hemoglobin is calculated based on the concentration detection according to the Beer-Lambert law using a dual-wavelength compensation algorithm at 540 nm and 570 nm.

6. The method for monitoring bleeding volume during hysteroscopic surgery according to claim 1, wherein: In step S4, an integral calculation is performed based on the calculated hemoglobin concentration data in combination with the real-time flow rate to obtain a second value of the bleeding volume.

7. The method for monitoring bleeding volume during hysteroscopic surgery according to claim 1, wherein: In step S5, weights are set for the first value and the second value data respectively, and the weights are dynamically adjusted according to the confidence level; the first value and the second value are weighted and summed to calculate the estimated bleeding volume.

8. The method for monitoring bleeding volume during hysteroscopic surgery according to claim 1, wherein: Set thresholds based on clinical data and divide them into several levels; set corresponding warnings and corresponding operating procedures for each level; The warning level is determined based on the calculated estimated bleeding volume and the corresponding warning and operating procedures are executed.

9. A hysteroscopic surgery bleeding volume monitoring system, using the method according to any one of claims 1 to 8 to monitor bleeding volume, characterized in that: It includes data acquisition module, data calculation module, data output module and communication module; The data acquisition module includes an image acquisition unit, a multispectral acquisition unit, and a monitoring unit; The image acquisition unit is used to acquire image data of the hysteroscope to facilitate subsequent analysis and processing to obtain the first value; The multi-spectral acquisition unit is arranged in the suction tube to measure the liquid flowing through the suction tube and calculate the second value of the bleeding volume through the hemoglobin concentration and flow rate; The data calculation module is used to process and calculate the data collected by the data acquisition unit and obtain the calculation results; The data output module is used to output the calculation results; The communication module is used for the system to communicate with various sensors and real-world devices, and to display calculation results in real time to help doctors quickly determine the amount of bleeding during surgery.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for monitoring bleeding volume during hysteroscopic surgery according to any one of claims 1 to 8 are implemented.

Images