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CN-120918787-B - Gynecological tumor multidisciplinary joint operation path planning system and method

CN120918787BCN 120918787 BCN120918787 BCN 120918787BCN-120918787-B

Abstract

The invention belongs to the technical field of path planning, and discloses a gynecological tumor multidisciplinary joint operation path planning system and method. The method comprises the steps of acquiring first focus image data from a gynecological tumor operation part, evaluating first physiological function parameters of a patient state, processing first operation state parameters of an operator to obtain first combined operation path planning characteristics, constructing a multi-disciplinary combined operation path planning model by using the first combined operation path planning characteristics and a corresponding first tumor operation planning method, inputting second combined operation path planning characteristics of an object to be operated into the model to obtain a second tumor operation planning method, and obtaining tumor operation path planning route suggestions by referring to physiological parameters such as images, brain electricity and the like, so as to assist the operator to select paths for a long time, reduce the fatigue degree and operation comfort degree of the operator, accurately manage operation paths and improve the operation completion rate.

Inventors

  • CAO YANG
  • WANG CHUANG
  • CHEN LIBIN

Assignees

  • 杭州市临安区第三人民医院(杭州市临安区第三人民医院医共体)

Dates

Publication Date
20260508
Application Date
20250808

Claims (8)

  1. 1. A method for planning a multidisciplinary joint surgical path for a gynecological tumor, the method comprising: collecting first focus image data from a gynecological tumor operation part, evaluating physiological function parameters of a patient state, and performing operation state parameter processing of an operator to obtain operation path planning characteristics; and collecting tumor surgery planning methods determined from the surgeon; constructing a first multidisciplinary joint surgery path planning model by utilizing the surgery path planning characteristics and the tumor surgery planning method; Before the operation path planning feature is acquired, generating focus image data of the first focus image data by utilizing an antagonism network model based on the improvement generation of the physiological function parameters to obtain second focus image data, generating a combined path planning feature based on the second focus image data, the physiological function parameters and the operation state parameters, and constructing a second multidisciplinary combined operation path planning model by utilizing the combined path planning feature and the tumor operation planning method.
  2. 2. A method of planning a multidisciplinary joint surgery path for a gynecological tumor as in claim 1, wherein: The focus image data is obtained through CT scanning, and the obtained focus image data is subjected to target focus data calculation and screening to obtain first focus image data or second focus image data, wherein the target focus data calculation and screening formula is as follows: In the middle of The obtained image data is processed based on gray values, and the obtained values are filtered by operators, namely the first focus image data or the second focus image data, 、 The gradient operator is represented by a gradient operator, In order to convolve the operation symbols, 、 、 For the image's coefficient of graying, 、 、 For the red-green-blue three channel pixel values of the image, Represents the maximum value taken by the gradient values in the horizontal and vertical directions, k is the number of pixel values greater than the maximum value taken, Indicating greater than or equal to Is a sum of pixel values of (a) and (b).
  3. 3. A method of planning a multidisciplinary joint surgery path for a gynecological tumor as in claim 1, wherein: The physiological function parameters are obtained by calculating the tumor size, the blood flow velocity at the tumor position, the blood oxygen saturation ratio and the respiratory frequency of a patient, and the calculation formula is as follows: In the middle of The parameters of the physiological function are used for generating the data, Setting the value of tumor size according to TNM stage, setting the value to be 0-3 according to the range of stage setting value, 、 The blood flow rate and the blood oxygen saturation at the tumor position are respectively, 、 The average blood flow velocity and the average blood oxygen saturation of the human body are respectively, For the respiratory rate of the patient, Is the normal female respiratory rate.
  4. 4. A method of planning a multidisciplinary joint surgery path for a gynecological tumor as in claim 1, wherein: The operation state parameters are obtained by processing blood flow rate, blood oxygen saturation, respiratory rate ratio and brain electrophysiological parameters of a doctor, and the calculation formula is as follows: In the middle of Represents the correction coefficient of the brain electric physiological parameter, Is the brain electrical average value, the unit is microvolts, Representing the parameters of the surgical status of the doctor, For the blood oxygen saturation of the doctor, For the blood flow rate of the doctor, For the respiratory rate of the doctor, For normal respiration rate of male and female, the value range of k is 0.15-0.25.
  5. 5. A method of planning a multidisciplinary joint surgery path for a gynecological tumor as in claim 1, wherein: An antagonism network model is generated by adopting the improvement of physiological function parameters, and focus image data is generated by optimizing and improving a discriminator thereof.
  6. 6. A method of planning a multidisciplinary joint surgery path for a gynecological tumor as in claim 5, wherein: an SVM model is employed for the first multi-disciplinary joint surgical path planning model or the second multi-disciplinary joint surgical path planning model.
  7. 7. The utility model provides a many disciplines of gynaecology's tumour joint surgery route planning system, includes tumour focus image data collection module, patient's state evaluation module, doctor's state evaluation module, operation route planning feature processing module, generates and fights network image generation module, many disciplines joint surgery route planning model construction module, many disciplines joint surgery route planning module, its characterized in that: the tumor focus image data collection module is used for collecting first focus image data from a gynecological tumor operation part; The patient state evaluation module is used for evaluating physiological function parameters of the patient state; The doctor state evaluation module is used for collecting operation state parameters of a doctor who performs operation; The surgical path planning feature processing module is used for receiving the first focus image data, the physiological function parameter and the surgical state parameter and processing to obtain a surgical path planning feature, and also used for receiving the second focus image data, the physiological function parameter and the surgical state parameter and processing to obtain a combined surgical path planning feature; generating focus image data of the first focus image data by utilizing an improved generation countermeasure network model based on the physiological function parameters to obtain second focus image data; The multi-disciplinary joint surgery path planning model construction module is used for constructing a first multi-disciplinary joint surgery path planning model according to the surgery path planning characteristics and a tumor surgery planning method, and also used for constructing a second multi-disciplinary joint surgery path planning model according to the joint surgery path planning characteristics and the tumor surgery planning method; The multidisciplinary joint surgery path planning module is used for generating a multidisciplinary joint surgery path planning method by utilizing the first multidisciplinary joint surgery path planning model or the second multidisciplinary joint surgery path planning model in the multidisciplinary joint surgery path planning model construction module so as to assist doctors in planning tumor surgery paths.
  8. 8. A gynecological tumor multidisciplinary joint surgery path planning system according to claim 7, wherein: An antagonism network model is generated by adopting the improvement of physiological function parameters, and focus image data is generated by optimizing and improving a discriminator thereof.

Description

Gynecological tumor multidisciplinary joint operation path planning system and method Technical Field The invention belongs to the technical field of path planning, and particularly relates to a path planning system and method for gynecological tumor multidisciplinary joint operation. Background The auxiliary operation under the guidance of the image becomes a research and development and application hot spot in the field of tumor operation, and the accurate, minimally invasive and intelligent development of tumor treatment is being accelerated. The image-based operation path planning method directly influences the man-machine interaction performance of tumor operation. Advanced planning of surgical paths is very common in oncology clinics. Early surgical path planning methods were mainly performed manually or semi-automatically by a physician on a software interactive interface. The operation method and the interaction interface have obvious engineering characteristics, are difficult to be well compatible with the existing operation habit of doctors, have lower operation efficiency, and are a bottleneck affecting the large-scale popularization and application of auxiliary operations. The statistical shape model method and the deep learning method provide possible solutions for exploring automatic planning and intelligent planning technologies for assisting tumor surgery paths. The existing automatic planning research of the tumor operation path based on the preoperative three-dimensional CT image and the deep neural network has preliminarily shown the potential advantages and application feasibility of the intelligent technology in the field of the automatic planning of the auxiliary tumor operation path of the multidisciplinary technology. Through the above analysis, the problems and defects existing in the prior art are as follows: in the conventional gynecological tumor operation path planning, only the state condition of a patient is considered, and in the case of less data volume of a specific tumor image and inaccurate generated data, the planning and design of a tumor operation path are performed, so as to help a doctor to perform the path planning of the tumor operation. How to obtain tumor operation path planning route suggestion by combining with the generation of images with higher accuracy and physiological parameters such as brain electricity, assist a long-time operation doctor in path selection, reduce doctor fatigue and operation comfort, accurately manage operation paths and improve operation completion rate. And how to adopt a machine learning method to carry out self-adaptive acquisition of a tumor operation path method, and how to simultaneously process different state conditions of a patient and a doctor, and carry out comprehensive acquisition of unified characteristics to reduce the operation judgment labor of the doctor for generating the operation path so as to generate the optimal tumor operation path, thereby carrying out accurate treatment of the tumor operation path on different patients. Disclosure of Invention In order to solve the technical problems, the invention provides a planning method and a planning system for a gynecological tumor multidisciplinary joint operation path. In a first aspect of the invention, there is provided a method of planning a gynaecological oncology multidisciplinary joint surgery path, the method comprising: collecting first focus image data from a gynecological tumor operation part, evaluating physiological function parameters of a patient state, and performing operation state parameter processing of an operator to obtain operation path planning characteristics; and collecting tumor surgery planning methods determined from the surgeon; and constructing a first multidisciplinary joint surgery path planning model by utilizing the surgery path planning characteristics and the tumor surgery planning method. Further, before the operation path planning feature is acquired, generating focus image data of the first focus image data by using an antagonism network model based on the improvement generation of the physiological function parameters to obtain second focus image data, generating a joint path planning feature based on the second focus image data, the physiological function parameters and the operation state parameters, and constructing a second multidisciplinary joint operation path planning model by using the joint operation path planning feature and the tumor operation planning method. Further, focus image data are obtained through CT scanning, and target focus data calculation screening is carried out on the obtained focus image data to obtain first focus image data or second focus image data. Further, the physiological function parameters are calculated by the tumor size of the patient, the blood flow rate at the tumor position, the blood oxygen saturation ratio and the respiratory frequency. Further, the operation state parameters are obtai