CN113729932A - Intelligent microwave ablation system for liver tumor - Google Patents

Intelligent microwave ablation system for liver tumor Download PDF

Info

Publication number
CN113729932A
CN113729932A CN202111153700.0A CN202111153700A CN113729932A CN 113729932 A CN113729932 A CN 113729932A CN 202111153700 A CN202111153700 A CN 202111153700A CN 113729932 A CN113729932 A CN 113729932A
Authority
CN
China
Prior art keywords
liver
information
unit
ablation
identification code
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202111153700.0A
Other languages
Chinese (zh)
Inventor
王武杰
周彤
常海洋
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Second Hospital of Shandong University
Original Assignee
Second Hospital of Shandong University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Second Hospital of Shandong University filed Critical Second Hospital of Shandong University
Priority to CN202111153700.0A priority Critical patent/CN113729932A/en
Publication of CN113729932A publication Critical patent/CN113729932A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B18/00Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
    • A61B18/18Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body by applying electromagnetic radiation, e.g. microwaves
    • A61B18/1815Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body by applying electromagnetic radiation, e.g. microwaves using microwaves
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06KGRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K17/00Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00ICT specially adapted for the handling or processing of medical images
    • G16H30/20ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00ICT specially adapted for the handling or processing of medical images
    • G16H30/40ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B18/00Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
    • A61B2018/00315Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body for treatment of particular body parts
    • A61B2018/00529Liver
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B18/00Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body
    • A61B2018/00571Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body for achieving a particular surgical effect
    • A61B2018/00577Ablation

Abstract

The invention is suitable for the technical field of medical treatment, provides an intelligent microwave ablation system for liver tumors, is used for intelligent microwave ablation of the liver tumors, and solves the problems that the position selection of a probe in the existing ablation method does not have any auxiliary system model, the ablation difficulty is increased, and the success rate of the operation is reduced; the method comprises the following steps: a liver feature information extraction module; the liver image three-dimensional reconstruction module is used for extracting the feature identification code; the microwave ablation simulation model establishing module is used for acquiring a reconstructed liver three-dimensional image; a microwave ablation real construction module extracts thermophysical parameters of the corresponding liver; the invention provides a liver feature information extraction module, a liver image three-dimensional reconstruction module and a microwave ablation real construction module, which are used for realizing the conversion from two dimensions to three dimensions of a liver image by extracting effective liver feature information, assisting medical staff to train a liver operation of a patient for multiple times by the microwave ablation real construction module and improving the success rate of the operation of the patient.

Description

Intelligent microwave ablation system for liver tumor
Technical Field
The invention belongs to the technical field of medical treatment, and particularly relates to an intelligent microwave ablation system for liver tumors.
Background
Primary liver cancer is a common malignant tumor with the morbidity and mortality rate in China ranked in the front, and about 38.3 thousands of people die of liver cancer every year, which is more than half of the death cases of liver cancer in the whole world. The current treatment methods of liver cancer include surgical resection, liver transplantation, local ablation, interventional therapy, radiotherapy, targeted therapy, immunobiotherapy and the like.
The microwave thermal ablation technology has the advantages of high temperature, strong tissue penetrability, large ablation range, minimal invasion, realization of multi-point ablation and the like, and has been widely applied and researched in the treatment of solid tumors such as liver cancer, lung cancer, kidney cancer and the like. The microwave ablation is incorporated into the national (NCCN) and national tumor treatment guidelines by the conventional tumor treatment technology, the clinical requirement on multi-needle combined ablation of liver tumors is high, the region fusion phenomenon of combined ablation lacks a corresponding model, and the probe position selection of the existing ablation method does not have any auxiliary system model, so that the ablation difficulty is increased, and the success rate of the operation is reduced.
Disclosure of Invention
The invention provides an intelligent microwave ablation system for liver tumors, and aims to solve the problems that no auxiliary system model is provided for probe position selection in the conventional ablation method, ablation difficulty is increased, and operation success rate is reduced.
The invention is realized in this way, an intelligent microwave ablation system for liver tumor is used for intelligent microwave ablation of liver tumor, the intelligent microwave ablation system for liver tumor includes:
the liver characteristic information extraction module is used for extracting a two-dimensional image and target text information of the liver, converting the two-dimensional image and the target text information into basic liver characteristic information, and calling the basic liver characteristic information and converting the basic liver characteristic information into a characteristic identification code;
the liver image three-dimensional reconstruction module is used for extracting the feature identification codes and matching the feature identification codes according to the liver image library;
the microwave ablation simulation model establishing module is used for acquiring a reconstructed liver three-dimensional image, calling an ablation simulation model, executing simulated ablation of liver three-dimensional image ablation through the ablation simulation model and acquiring corresponding thermophysical parameters of the liver;
and the microwave ablation real construction module extracts the corresponding thermophysical parameters of the liver and carries out actual ablation according to the thermophysical parameters of the liver.
Preferably, the liver feature information extraction module includes:
the two-dimensional image acquisition unit is used for acquiring two-dimensional image information of the abdomen of the patient and transmitting the information to the front-end control unit;
the target text information acquisition unit is used for acquiring target text information and transmitting the target text information to the front-end control unit;
the front-end control unit is used for acquiring data information of the two-dimensional image acquisition unit and the target text information acquisition unit and converting the data information of the two-dimensional image acquisition unit and the target text information acquisition unit into liver characteristic basic information data;
and the identification code conversion unit is used for calling the liver characteristic basic information data and converting the liver characteristic basic information data into the characteristic identification code to form a target information stream.
Preferably, the front end control unit includes:
the acquisition control module is used for acquiring data information streams of the original two-dimensional image acquisition unit and the target text information acquisition unit;
the classification control module is used for classifying, dividing and grading the data information flow;
the segmentation control module is used for segmenting the data information flow into at least one group of information flows according to the division rating;
and the front-end sending control module is used for sending the segmented packet information flow to the identification code conversion unit.
Preferably, the identification code conversion unit includes:
the identification recognition unit is used for acquiring a unique equipment identification code of the two-dimensional image acquisition unit or the target text information acquisition unit, taking the equipment identification code as a security token, and establishing transcoding connection after the equipment identification code passes the verification;
and the transcoding information acquisition unit is used for inputting the equipment identification code, extracting the characteristic information in the information stream and transcoding the characteristic information in the information stream based on transcoding connection.
Preferably, the liver image three-dimensional reconstruction module comprises:
a feature identification code acquisition unit for extracting a feature identification code;
the liver image library calling unit is used for calling a standard comparison feature code in the liver image library;
the characteristic identification code traversing unit is used for matching the extracted characteristic identification code according to the standard comparison characteristic code in the liver image library, and comparing a preset response threshold value of the identification code preset in the liver image library with a comparison response value to obtain a characteristic identification code with high responsiveness;
and the identification code analysis and classification unit extracts the characteristic identification codes with high responsivity, screens out the characteristic identification codes with low responsivity, and executes a liver image library three-dimensional reconstruction protocol to obtain a reconstructed liver three-dimensional image.
Preferably, the feature identifier traversal unit includes:
the preset response threshold setting unit is used for setting a preset response threshold according to the liver standard image library;
the response value comparison unit is used for calculating a preset response threshold value of the preset identification code of the liver image library, calculating a comparison response value at the same time, and comparing the preset response threshold value of the preset identification code of the liver image library with the comparison response value;
and a highly responsive transmitting unit that transmits the characteristic identification code having high responsiveness.
Preferably, the microwave ablation simulation model building module comprises:
the reconstruction unit acquisition unit is used for acquiring a reconstructed liver three-dimensional image;
the simulation model calling unit is used for calling the ablation simulation model;
and the simulation model execution unit executes the simulated ablation of the liver three-dimensional image ablation through the ablation simulation model to obtain the corresponding thermophysical property parameters of the liver.
Preferably, the simulation model execution unit includes:
the simulation instruction input module is used for acquiring an execution protocol of the ablation simulation model and acquiring a simulation instruction according to the execution protocol;
the simulation instruction execution module acquires an execution protocol to obtain a simulation instruction and executes the simulation instruction;
the simulation image acquisition unit is used for acquiring a simulated liver three-dimensional image according to the executed simulation instruction;
and the simulated ablation establishing unit is used for obtaining simulated ablation of the liver three-dimensional image ablation based on the simulated liver three-dimensional image and acquiring the corresponding thermophysical property parameters of the liver.
Preferably, the microwave ablation real construction module comprises:
the thermophysical property parameter extraction unit is used for extracting thermophysical property parameters of the corresponding liver;
and the real ablation execution unit is used for carrying out actual ablation based on the thermophysical parameters of the liver.
Preferably, the feature information in the information stream is extracted, and the feature information in the information stream includes an original data ID, a partition block ID, an original data format, an acquisition time, and an acquisition unit type.
Compared with the prior art, the embodiment of the application mainly has the following beneficial effects:
the invention provides an intelligent microwave ablation system for liver tumors, which comprises a liver characteristic information extraction module, a liver image three-dimensional reconstruction module and a microwave ablation real construction module, wherein effective liver characteristic information is extracted to realize conversion of two-dimensional to three-dimensional of a liver image, and the microwave ablation real construction module is used for assisting medical staff to train liver operations of a patient for multiple times, so that the success rate of the operations of the patient is improved.
Drawings
Fig. 1 is a schematic structural diagram of an intelligent microwave ablation system for liver tumors provided by the invention.
Fig. 2 is a schematic structural diagram of a liver feature information extraction module provided by the present invention.
Fig. 3 is a schematic structural diagram of a front-end control unit provided by the present invention.
Fig. 4 is a schematic structural diagram of an identification code conversion unit provided by the present invention.
Fig. 5 is a schematic structural diagram of a liver image three-dimensional reconstruction module provided by the invention.
Fig. 6 is a schematic structural diagram of a traversal unit for a signature provided by the present invention.
Fig. 7 is a schematic structural diagram of a microwave ablation simulation model building module provided by the invention.
FIG. 8 is a schematic structural diagram of a simulation model execution unit provided in the present invention.
Fig. 9 is a schematic structural diagram of the microwave ablation real building block provided by the invention.
Fig. 10 is a schematic structural flow chart for implementing the intelligent microwave ablation method for liver tumors provided by the invention.
Fig. 11 is a schematic view of a specific flow structure for extracting a two-dimensional image of a liver and target text information according to the present invention.
Fig. 12 is a schematic structural diagram of a specific flow of the operation of the three-dimensional reconstruction module for liver images provided by the present invention.
Description of reference numerals: 100-liver feature information extraction module, 110-two-dimensional image acquisition unit, 120-target text information acquisition unit, 130-front end control unit, 131-acquisition control module, 132-classification control module, 133-segmentation control module, 134-front end sending control module, 140-identification code conversion unit, 141-identification unit, 142-transcoding information acquisition unit, 200-liver image three-dimensional reconstruction module, 210-feature identification code acquisition unit, 220-liver image library retrieval unit, 230-feature identification code traversal unit, 231-preset response threshold setting unit, 232-response value comparison unit, 233-high responsiveness sending unit, 240-identification code analysis and classification unit, 300-microwave ablation simulation model establishment module, 310-a reconstruction unit obtaining unit, 320-a simulation model retrieving unit, 330-a simulation model executing unit, 331-a simulation instruction input module, 332-a simulation instruction executing module, 333-a simulation image obtaining unit, 334-a simulated ablation establishing unit, 400-a microwave ablation real constructing module, 410-a thermophysical property parameter extracting unit and 420-a real ablation executing unit.
Detailed Description
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "including" and "having," and any variations thereof, in the description and claims of this application and the description of the above figures are intended to cover non-exclusive inclusions. The terms "first," "second," and the like in the description and claims of this application or in the above-described drawings are used for distinguishing between different objects and not for describing a particular order.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
An embodiment of the present invention provides an intelligent microwave ablation system for liver tumor, as shown in fig. 1, the intelligent microwave ablation system for liver tumor includes:
the liver feature information extraction module 100 is configured to extract a two-dimensional image of a liver and target text information, convert the two-dimensional image and the target text information into liver feature basic information, and convert the liver feature basic information into a feature identification code.
In this embodiment, the two-dimensional image of the liver is acquired by magnetic resonance, X-ray irradiation and B-ultrasonic molding, and meanwhile, it can be understood that the two-dimensional image at least includes images of the front side, the rear side and the side of the abdomen of the patient, so as to ensure the accuracy of the acquired image, and then the characteristic information of the two-dimensional image is acquired.
In this embodiment, the target text information is pathological information of a patient, wherein the pathological information is body index data of the patient at intervals, and it can be understood that the body index data of the patient is sex, disease age, number of visits, liver cirrhosis index, hepatitis b index, alpha fetoprotein, oncofetal protein, height, weight, BMI, Child-trough score, hepatitis b history, hepatitis c history, portal hypertension, drinking condition, hemoglobin, platelets, leukocytes, neutrophil ratio, lymphocyte ratio, NLR, monocyte ratio, eosinophil ratio, basophil ratio, total bilirubin, direct bilirubin, aspartate aminotransferase, glutamate aminotransferase, albumin, urea, creatinine, cystatin, prothrombin time, activated partial thromboplastin time, tumor number, maximum tumor size, total tumor size, tumor size, Tumor location, macroscopic vascular invasion, lymphatic metastasis location, treatment history, recurrence history.
And the liver image three-dimensional reconstruction module 200 is used for extracting the feature identification codes and matching the feature identification codes according to the liver image library.
In this embodiment, the liver image is reconstructed by extracting the feature identification code, so that the conversion from two dimensions to three dimensions of the liver image is realized, the medical staff is assisted to train the liver operation of the patient for many times, the success rate of the liver operation of the patient is improved, and it can be understood that the medical staff determines the number of the probes and the positions of the probes according to the reconstructed liver image.
The microwave ablation simulation model establishing module 300 is configured to acquire a reconstructed liver three-dimensional image, call an ablation simulation model, perform simulated ablation of the liver three-dimensional image ablation through the ablation simulation model, and acquire thermophysical parameters of the corresponding liver.
In the embodiment, the insertion position of the probe is guided by establishing the microwave ablation simulation model, so that the success rate of the operation is ensured, and the pain of a patient is reduced.
The microwave ablation real construction module 400 extracts the corresponding thermophysical parameters of the liver, and performs actual ablation according to the thermophysical parameters of the liver.
In a further preferred embodiment of the present invention, as shown in fig. 2, the liver feature information extracting module 100 includes:
a two-dimensional image collecting unit 110 for collecting two-dimensional image information of the abdomen of the patient and transmitting the information to the front-end control unit 130;
in the embodiment of the present invention, the two-dimensional image acquisition unit 110 is a combination of an image sensor and an imaging instrument, the imaging instrument is a common magnetic resonance medical device, the image sensor is configured to acquire an image acquired by the imaging instrument and preprocess the image, and it can be understood that the image preprocessing manner includes, but is not limited to, light compensation of the image, processing of image gray scale, and image denoising processing.
And a target text information collecting unit 120, configured to collect target text information and transmit the target text information to the front-end control unit 130.
In the embodiment of the invention, the target text information is collected from the shared data uploaded to the shared cloud end by each hospital, so that the condition of the patient can be conveniently judged, and if medical staff need to obtain the shared information, authorization codes need to be obtained from the patient and the shared cloud end, so that the privacy safety of the patient is ensured.
The front-end control unit 130 acquires data information of the two-dimensional image acquisition unit 110 and the target text information acquisition unit 120, and converts the data information of the two-dimensional image acquisition unit 110 and the target text information acquisition unit 120 into liver feature basic information data.
In the embodiment of the present invention, the front-end control unit 130 is capable of acquiring data information of the two-dimensional image acquisition unit 110 and the target text information acquisition unit 120, and converting the acquired data information of the two-dimensional image acquisition unit 110 and the target text information acquisition unit 120 into liver feature basic information data.
The identifier conversion unit 140 retrieves the liver feature basic information data, and converts the liver feature basic information data into a feature identifier to form a target information stream.
In a further preferred embodiment of the present invention, as shown in fig. 3, the front-end control unit 130 includes:
an acquisition control module 131, configured to acquire data information streams of the original two-dimensional image acquisition unit 110 and the target text information acquisition unit 120;
a classification control module 132, configured to classify, classify and rate the data information stream;
a division control module 133, which divides the data information stream into at least one group of information streams according to the division rating;
the front-end transmission control module 134 is configured to transmit the segmented packet information stream to the identifier conversion unit 140.
In this embodiment, when classifying and rating the data information stream, rating the data based on the data highlighting priority order, where the rating order is: the optimal, preferential, common preferential and normal processing levels are achieved, the data are graded through grading, and the work composition of the system is reduced.
In a further preferred embodiment of the present invention, as shown in fig. 4, the identification code conversion unit 140 includes:
the identification recognition unit 141 acquires a unique device identification code of the two-dimensional image acquisition unit 110 or the target text information acquisition unit 120, the device identification code is used as a security token, and a transcoding connection is established after the verification is passed;
and the transcoding information acquisition unit 142 is used for inputting the equipment identification code, extracting the characteristic information in the information stream, and transcoding the characteristic information in the information stream based on transcoding connection, wherein the characteristic information in the information stream comprises an original data ID, a partition block ID, an original data format, acquisition time and an acquisition unit type.
In this embodiment, the identification recognition unit 141 can acquire the unique device identification code of each group of the two-dimensional image acquisition unit 110 or the target text information acquisition unit 120 during operation, and the device identification code is used as a security token to establish transcoding connection after the approval is passed.
In a further preferred embodiment of the present invention, as shown in fig. 5, the liver image three-dimensional reconstruction module 200 includes:
a feature identification code obtaining unit 210 for extracting a feature identification code;
a liver image library retrieving unit 220, configured to retrieve a standard comparison feature code in the liver image library;
the feature recognition code traversing unit 230 compares the extracted feature recognition code according to the standard comparison feature code in the liver image library, and compares a preset response threshold value of the feature recognition code preset in the liver image library with the comparison response value to obtain a feature recognition code with high responsiveness;
and the identification code analyzing and classifying unit 240 extracts the characteristic identification codes with high responsivity, screens out the characteristic identification codes with low responsivity, and executes a liver image library three-dimensional reconstruction protocol to obtain a reconstructed liver three-dimensional image.
In this embodiment, the feature identification code obtaining unit 210 includes a data receiver, the data receiver receives the feature identification code based on a communication connection mode, the communication connection type is a bluetooth mode or a data connection mode, the liver image library retrieving unit 220 considers the retrieval priority based on the rating result and the segmentation result of the identification code, compares the predetermined response threshold of the identification code with the comparison response value through the liver image library to obtain the feature identification code with high responsiveness, and obtains the reconstructed three-dimensional liver image by executing a three-dimensional reconstruction protocol of the liver image library.
In a further preferred embodiment of the present invention, as shown in fig. 6, the signature traversal unit 230 includes:
a preset response threshold setting unit 231 that sets a preset response threshold according to the liver standard image library;
the response value comparison unit 232 calculates a preset response threshold of the preset identification code of the liver image library, calculates a comparison response value at the same time, and compares the preset response threshold of the preset identification code of the liver image library with the comparison response value;
high-responsiveness transmitting section 233 transmits a feature identification code with high responsiveness.
In this embodiment, the high-responsiveness sending unit 233 improves the work efficiency of the identification code analysis and classification unit 240 by sending the characteristic identification code with high responsiveness, and simultaneously screens out redundant interference factors, thereby improving the accuracy of the microwave ablation simulation model.
In a further preferred embodiment of the present invention, as shown in fig. 7, the microwave ablation simulation modeling module 300 includes:
a reconstruction unit obtaining unit 310, configured to obtain a reconstructed liver three-dimensional image;
a simulation model retrieving unit 320 for retrieving an ablation simulation model;
the simulation model executing unit 330 executes simulated ablation of liver three-dimensional image ablation through the ablation simulation model to obtain corresponding thermophysical parameters of the liver.
In this embodiment, the reconstruction unit obtaining unit 310 obtains a reconstructed three-dimensional image of a liver, and the simulation model obtaining unit 320 obtains an ablation simulation model, sends a simulation model execution instruction, and executes simulated ablation of the three-dimensional image of the liver through the ablation simulation model to obtain a corresponding thermophysical property parameter of the liver.
In a further preferred embodiment of the present invention, as shown in fig. 8, the simulation model executing unit 330 includes:
the simulation instruction input module 331 is configured to obtain an execution protocol of the ablation simulation model, and obtain a simulation instruction according to the execution protocol;
the simulation instruction execution module 332 acquires the execution protocol to obtain the simulation instruction and executes the simulation instruction;
the simulated image obtaining unit 333 obtains a simulated three-dimensional image of the liver according to the executed simulation instruction;
the simulated ablation establishing unit 334 is configured to obtain simulated ablation of the liver three-dimensional image ablation based on the simulated liver three-dimensional image, and obtain thermophysical parameters of the corresponding liver.
The simulation instruction execution module 332 executes an operation simulation operation instruction, the simulation instruction execution module 332 simulates the state of the liver in the liver operation, extracts the data of the porous area, the wound area, the tumor state and the blood flow of the liver, obtains the simulated ablation of the three-dimensional liver image based on the simulated three-dimensional liver image, and obtains the thermophysical property parameters of the corresponding liver.
In a further preferred embodiment of the present invention, as shown in fig. 9, the microwave ablation real building block 400 comprises:
a thermophysical parameter extraction unit 410 for extracting thermophysical parameters of the corresponding liver;
the real ablation executing unit 420 performs the actual ablation based on the thermophysical parameters according to the liver.
The thermophysical parameter defines a division rule of the real ablation execution unit 420, sets a risk margin condition, predicts the risk of the operation step based on the thermophysical parameter, guides the next operation, executes the next operation if the risk value is lower than the preset risk margin condition, terminates the operation if the risk value is higher than the preset risk margin condition, generates report feedback, and transmits the feedback report to the liver feature information extraction module 100.
The embodiment of the invention also provides an intelligent microwave ablation method for liver tumors, and fig. 10 shows specific steps of implementing the intelligent microwave ablation method for liver tumors, and the implementation steps of the intelligent microwave ablation method for liver tumors specifically include:
s100, extracting a two-dimensional image and target text information of the liver, converting the two-dimensional image and the target text information into liver characteristic basic information, and calling the liver characteristic basic information and converting the liver characteristic basic information into a characteristic identification code.
And S200, extracting the feature identification code, and matching the feature identification code according to the liver image library.
S300, acquiring the reconstructed liver three-dimensional image, calling an ablation simulation model, executing simulated ablation of the liver three-dimensional image ablation through the ablation simulation model, and acquiring the thermophysical property parameters of the corresponding liver.
S400, extracting the corresponding thermophysical parameters of the liver, and performing actual ablation according to the thermophysical parameters of the liver.
Fig. 11 shows a specific step of extracting a two-dimensional image of a liver and target text information, where the specific step of extracting the two-dimensional image of the liver and the target text information includes:
s101, acquiring two-dimensional image information of the abdomen of the patient, and transmitting the information to the front-end control unit 130.
S102, collecting the target text information, and transmitting the target text information to the front-end control unit 130.
And S103, acquiring data information of the two-dimensional image acquisition unit 110 and the target text information acquisition unit 120, and converting the acquired data information of the two-dimensional image acquisition unit 110 and the target text information acquisition unit 120 into liver feature basic information data.
And S104, calling the liver characteristic basic information data, and converting the liver characteristic basic information data into a characteristic identification code to form a target information stream.
Fig. 12 shows specific steps of the operation of the liver image three-dimensional reconstruction module 200, and the implementation steps of the liver image three-dimensional reconstruction module 200 specifically include:
s201, extracting the feature identification code.
And S202, calling a standard comparison feature code in the liver image library.
And S203, matching the extracted feature identification code according to the standard comparison feature code in the liver image library, and comparing the preset response threshold value of the identification code in the liver image library with the comparison response value to obtain the feature identification code with high responsiveness.
And S204, extracting the feature identification codes with high responsivity, screening out the feature identification codes with low responsivity, and executing a three-dimensional reconstruction protocol of the liver image library to obtain a reconstructed liver three-dimensional image.
The invention also provides a readable storage medium having stored thereon a computer program which, when executed by a processor, causes the processor to perform the steps of the intelligent microwave ablation method for liver tumors.
Illustratively, a computer program can be partitioned into one or more modules, which are stored in memory and executed by a processor to implement the present invention. One or more of the modules may be a series of computer program instruction segments capable of performing certain functions, which are used to describe the execution of the computer program in the terminal device.
Those skilled in the art will appreciate that the above description of the terminal device is merely exemplary and not limiting, and that more or fewer components than those described above may be included, or certain components may be combined, or different components may be included, such as input output devices, network access devices, buses, etc.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is the control center of the terminal equipment and connects the various parts of the entire user terminal using various interfaces and lines.
The memory may be used to store computer programs and/or modules, and the processor may implement various functions of the terminal device by operating or executing the computer programs and/or modules stored in the memory and calling data stored in the memory. The memory may mainly include a program storage area and a data storage area, where the program storage area may store an operating system, an application program required by at least one function (such as an information collection template presentation function, a product information distribution function, and the like), and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
The terminal device integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the modules/units in the system according to the above embodiments may be implemented by a computer program, which may be stored in a computer-readable storage medium and used by a processor to implement the functions of the system embodiments. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, U.S. disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution media, and the like.
In summary, the invention provides an intelligent microwave ablation system for liver tumor, which comprises a liver feature information extraction module, a liver image three-dimensional reconstruction module and a microwave ablation real construction module, wherein effective liver feature information is extracted to realize conversion of two-dimensional to three-dimensional of a liver image, and the microwave ablation real construction module assists medical staff to train a liver operation of a patient for many times, so that the success rate of the patient operation is improved.
It should be noted that, for simplicity of description, the above-mentioned embodiments are described as a series of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required by the invention.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the above-described division of the units is only one type of division of logical functions, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or communication connection may be an indirect coupling or communication connection between devices or units through some interfaces, and may be in a telecommunication or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
The above examples are only used to illustrate the technical solutions of the present invention, and do not limit the scope of the present invention. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from these embodiments without making any inventive step, fall within the scope of the present invention. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art may still make various combinations, additions, deletions or other modifications of the features of the embodiments of the present invention according to the situation without conflict, so as to obtain different technical solutions without substantially departing from the spirit of the present invention, and these technical solutions also fall within the protection scope of the present invention.

Claims (10)

1. An intelligent microwave ablation system for liver tumors, comprising:
the liver characteristic information extraction module is used for extracting a two-dimensional image and target text information of the liver, converting the two-dimensional image and the target text information into basic liver characteristic information, and calling the basic liver characteristic information and converting the basic liver characteristic information into a characteristic identification code;
the liver image three-dimensional reconstruction module is used for extracting the feature identification codes and matching the feature identification codes according to the liver image library;
the microwave ablation simulation model establishing module is used for acquiring a reconstructed liver three-dimensional image, calling an ablation simulation model, executing simulated ablation of liver three-dimensional image ablation through the ablation simulation model and acquiring corresponding thermophysical parameters of the liver;
and the microwave ablation real construction module extracts the corresponding thermophysical parameters of the liver and carries out actual ablation according to the thermophysical parameters of the liver.
2. The intelligent microwave ablation system for liver tumors of claim 1, wherein the liver feature information extraction module comprises:
the two-dimensional image acquisition unit is used for acquiring two-dimensional image information of the abdomen of the patient and transmitting the information to the front-end control unit;
the target text information acquisition unit is used for acquiring target text information and transmitting the target text information to the front-end control unit;
the front-end control unit is used for acquiring data information of the two-dimensional image acquisition unit and the target text information acquisition unit and converting the data information of the two-dimensional image acquisition unit and the target text information acquisition unit into liver characteristic basic information data;
and the identification code conversion unit is used for calling the liver characteristic basic information data and converting the liver characteristic basic information data into the characteristic identification code to form a target information stream.
3. The intelligent microwave ablation system for liver tumors of claim 2, wherein the front end control unit comprises:
the acquisition control module is used for acquiring data information streams of the original two-dimensional image acquisition unit and the target text information acquisition unit;
the classification control module is used for classifying, dividing and grading the data information flow;
the segmentation control module is used for segmenting the data information flow into at least one group of information flows according to the division rating;
and the front-end sending control module is used for sending the segmented packet information flow to the identification code conversion unit.
4. The intelligent microwave ablation system for liver tumors of claim 3, wherein the identification code conversion unit comprises:
the identification recognition unit is used for acquiring a unique equipment identification code of the two-dimensional image acquisition unit or the target text information acquisition unit, taking the equipment identification code as a security token, and establishing transcoding connection after the equipment identification code passes the verification;
and the transcoding information acquisition unit is used for inputting the equipment identification code, extracting the characteristic information in the information stream and transcoding the characteristic information in the information stream based on transcoding connection.
5. The intelligent microwave ablation system for liver tumors of claim 4, wherein the liver image three-dimensional reconstruction module comprises:
a feature identification code acquisition unit for extracting a feature identification code;
the liver image library calling unit is used for calling a standard comparison feature code in the liver image library;
the characteristic identification code traversing unit is used for matching the extracted characteristic identification code according to the standard comparison characteristic code in the liver image library, and comparing a preset response threshold value of the identification code preset in the liver image library with a comparison response value to obtain a characteristic identification code with high responsiveness;
and the identification code analysis and classification unit extracts the characteristic identification codes with high responsivity, screens out the characteristic identification codes with low responsivity, and executes a liver image library three-dimensional reconstruction protocol to obtain a reconstructed liver three-dimensional image.
6. The intelligent microwave ablation system for liver tumors of claim 5, wherein the signature traversal unit comprises:
the preset response threshold setting unit is used for setting a preset response threshold according to the liver standard image library;
the response value comparison unit is used for calculating a preset response threshold value of the preset identification code of the liver image library, calculating a comparison response value at the same time, and comparing the preset response threshold value of the preset identification code of the liver image library with the comparison response value;
and a highly responsive transmitting unit that transmits the characteristic identification code having high responsiveness.
7. The intelligent microwave ablation system for liver tumors of any one of claims 1-6, wherein the microwave ablation simulation model building module comprises:
the reconstruction unit acquisition unit is used for acquiring a reconstructed liver three-dimensional image;
the simulation model calling unit is used for calling the ablation simulation model;
and the simulation model execution unit executes the simulated ablation of the liver three-dimensional image ablation through the ablation simulation model to obtain the corresponding thermophysical property parameters of the liver.
8. The intelligent microwave ablation system for liver tumors of claim 7, wherein the simulation model executing unit comprises:
the simulation instruction input module is used for acquiring an execution protocol of the ablation simulation model and acquiring a simulation instruction according to the execution protocol;
the simulation instruction execution module acquires an execution protocol to obtain a simulation instruction and executes the simulation instruction;
the simulation image acquisition unit is used for acquiring a simulated liver three-dimensional image according to the executed simulation instruction;
and the simulated ablation establishing unit is used for obtaining simulated ablation of the liver three-dimensional image ablation based on the simulated liver three-dimensional image and acquiring the corresponding thermophysical property parameters of the liver.
9. The intelligent microwave ablation system for liver tumors of claim 7, wherein the microwave ablation real construction module comprises:
the thermophysical property parameter extraction unit is used for extracting thermophysical property parameters of the corresponding liver;
and the real ablation execution unit is used for carrying out actual ablation based on the thermophysical parameters of the liver.
10. The intelligent microwave ablation system for liver tumors of claim 4, wherein the characteristic information in the information stream is extracted, and the characteristic information in the information stream comprises original data ID, segmentation block ID, original data format, acquisition time, and acquisition unit type.
CN202111153700.0A 2021-09-29 2021-09-29 Intelligent microwave ablation system for liver tumor Pending CN113729932A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111153700.0A CN113729932A (en) 2021-09-29 2021-09-29 Intelligent microwave ablation system for liver tumor

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111153700.0A CN113729932A (en) 2021-09-29 2021-09-29 Intelligent microwave ablation system for liver tumor

Publications (1)

Publication Number Publication Date
CN113729932A true CN113729932A (en) 2021-12-03

Family

ID=78741849

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111153700.0A Pending CN113729932A (en) 2021-09-29 2021-09-29 Intelligent microwave ablation system for liver tumor

Country Status (1)

Country Link
CN (1) CN113729932A (en)

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104856755A (en) * 2014-02-26 2015-08-26 西门子公司 System And Method For Personalized Computation Of Tissue Ablation Extent Based On Medical Images
CN105286988A (en) * 2015-10-12 2016-02-03 北京工业大学 CT image-guided liver tumor thermal ablation needle location and navigation system
CN107510503A (en) * 2016-06-16 2017-12-26 平安微创(北京)医药科技有限公司 A kind of microwave ablation simulation system
CN107833631A (en) * 2017-11-20 2018-03-23 新乡医学院 A kind of medical image computer-aided analysis method
WO2018069736A1 (en) * 2016-10-14 2018-04-19 Axial Medical Printing Limited A method for generating a 3d physical model of a patient specific anatomic feature from 2d medical images
CN112998849A (en) * 2021-02-08 2021-06-22 南京航空航天大学 Microwave conformal ablation method based on multi-needle combination

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104856755A (en) * 2014-02-26 2015-08-26 西门子公司 System And Method For Personalized Computation Of Tissue Ablation Extent Based On Medical Images
CN105286988A (en) * 2015-10-12 2016-02-03 北京工业大学 CT image-guided liver tumor thermal ablation needle location and navigation system
CN107510503A (en) * 2016-06-16 2017-12-26 平安微创(北京)医药科技有限公司 A kind of microwave ablation simulation system
WO2018069736A1 (en) * 2016-10-14 2018-04-19 Axial Medical Printing Limited A method for generating a 3d physical model of a patient specific anatomic feature from 2d medical images
CN107833631A (en) * 2017-11-20 2018-03-23 新乡医学院 A kind of medical image computer-aided analysis method
CN112998849A (en) * 2021-02-08 2021-06-22 南京航空航天大学 Microwave conformal ablation method based on multi-needle combination

Similar Documents

Publication Publication Date Title
CN111275080B (en) Artificial intelligence-based image classification model training method, classification method and device
JP6220310B2 (en) Medical image information system, medical image information processing method, and program
CN110136809A (en) A kind of medical image processing method, device, electromedical equipment and storage medium
CN110310281A (en) Lung neoplasm detection and dividing method in a kind of Virtual Medical based on Mask-RCNN deep learning
TW202105407A (en) Systems and methods for automated and interactive analysis of bone scan images for detection of metastases
CN104881568A (en) Cloud computation based early oncotherapy efficacy evaluation system and method
CN111128328A (en) Nasopharyngeal carcinoma structured image report and data processing system and method
CN102737250A (en) Method and system for automatic detection of spinal bone lesions in 3d medical image data
US20210033599A1 (en) Information processing apparatus, control method, and program
CN109524120A (en) Calculation method, system, equipment and storage medium are extracted in clinical data automation
US20230052133A1 (en) Medical image processing method and apparatus, device, storage medium, and product
CN108416190A (en) Tumour methods for screening, device, equipment and medium based on deep learning
CN109192261A (en) Information processing method and device, electronic equipment and storage medium
CN112545562A (en) Multimodal multiparameter breast cancer screening system, device and computer storage medium
CN112926677A (en) Information labeling method, device and system for medical image data
CN110223761B (en) Outlining data import method and device, electronic equipment and storage medium
CN107256344A (en) Data processing method, device and radiotherapy management system
CN113729932A (en) Intelligent microwave ablation system for liver tumor
KR20180051267A (en) Apparatus and method for measuring bone level
CN113435469A (en) Kidney tumor enhanced CT image automatic identification system based on deep learning and training method thereof
CN108335732A (en) A kind of the case recommendation method and its system of OCT images
CN114822690A (en) Multi-class multifunctional intelligent classification method applied to whole genome expression profile data
Megalooikonomou et al. Medical data fusion for telemedicine
CN102028494B (en) Method and system for processing cerebral perfusion image sequence
Zhu et al. Three-dimensional vasculature reconstruction of tumour microenvironment via local clustering and classification

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination