Cerebral hemorrhage treatment device and system based on noninvasive ultrasound

Abstract

The embodiment of the invention provides a cerebral hemorrhage treatment device and system based on noninvasive ultrasound, and the device comprises an image transmission module which is used for obtaining a brain tissue image and a cerebrovascular image; the intelligent hematoma positioning module is used for determining hematoma position information according to the brain tissue image and the cerebrovascular image; determining an ultrasonic irradiation path according to the hematoma position information, the brain tissue image and the cerebrovascular image; the ultrasonic intervention module is used for setting parameters of ultrasonic equipment; the ultrasonic monitoring module is used for acquiring state data of cerebral hemorrhage hematoma parts, edema degrees around hematoma, intracranial pressure, optic nerve sheaths and deep vein thrombosis; and the intelligent auxiliary decision-making module is used for determining an ultrasonic irradiation scheme according to the ultrasonic irradiation path and the parameters and state data of the ultrasonic equipment. Through the non-invasive ultrasonic cerebral hemorrhage treatment device, the cerebral hemorrhage hematoma absorption rate and efficiency can be improved, and finally the disability rate and the fatality rate of cerebral hemorrhage are reduced.

Description

Technical Field

[0001] This document relates to the field of medical device technology, and in particular to a non-invasive ultrasound-based cerebral hemorrhage treatment device and system. Background Art

[0002] Cerebral hemorrhage is one of the diseases with the highest disability and mortality rates worldwide. How to effectively reduce the disability and mortality rates of cerebral hemorrhage and improve the functional prognosis of cerebral hemorrhage has become a hot topic and difficulty in this field.

[0003] The conventional surgical hematoma removal treatments for cerebral hemorrhage are craniotomy hematoma removal and minimally invasive hematoma removal.

[0004] The biggest drawback of the above methods is that they cause brain tissue damage during the treatment process. Therefore, in this context, the advantages and necessity of non-invasive hematoma removal technology are particularly prominent. Summary of the invention

[0005] In view of the above scheme, the present application aims to propose a cerebral hemorrhage treatment device and system based on non-invasive ultrasound to achieve non-invasive removal of hematoma.

[0006] In a first aspect, one or more embodiments of this specification provide a non-invasive ultrasound-based cerebral hemorrhage treatment device, comprising:

[0007] An image transmission module, used to obtain brain tissue images and cerebral blood vessel images;

[0008] An intelligent hematoma positioning module, used to determine the location information of the hematoma according to the brain tissue image and the cerebral blood vessel image; and determine the ultrasound irradiation path according to the location information of the hematoma, the brain tissue image and the cerebral blood vessel image;

[0009] Ultrasound intervention module, used to set the parameters of the ultrasound equipment;

[0010] Ultrasound monitoring module, used to obtain data on the location of cerebral hemorrhage and hematoma, degree of edema around the hematoma, intracranial pressure, optic nerve sheath and status of deep vein thrombosis; and

[0011] The intelligent auxiliary decision-making module is used to determine the ultrasound irradiation plan according to the ultrasound irradiation path, the parameters of the ultrasound equipment and the status data.

[0012] Furthermore, the image transmission module is configured as follows:

[0013] The brain tissue image and the cerebral blood vessel image are acquired from an imaging workstation via a wired network or a wireless network.

[0014] Further, the intelligent hematoma positioning module is configured as follows:

[0015] Determining tissue space information around the hematoma according to the brain tissue image and the cerebral blood vessel image; and

[0016] The ultrasound irradiation path is determined based on the location information of the hematoma and the tissue space information.

[0017] Further, the ultrasound intervention module is configured to:

[0018] Set the ultrasound intervention frequency and ultrasound intervention time.

[0019] In a second aspect, the embodiment of the present application provides a non-invasive ultrasound-based cerebral hemorrhage treatment system, comprising:

[0020] The non-invasive ultrasound-based cerebral hemorrhage treatment device according to any one of the first aspects;

[0021] Artificial intelligence module, used to identify lesion information;

[0022] A telemedicine module, used for determining an ultrasound irradiation plan according to remote guidance;

[0023] A power module, used to supply power to the system; and

[0024] A cloud platform management module is used to connect the artificial intelligence module, the non-invasive ultrasonic cerebral hemorrhage treatment device, the telemedicine module and the power module.

[0025] Furthermore, the system comprises:

[0026] The ultrasonic probe fixing frame comprises two ultrasonic probes and an ultrasonic head frame, and the two ultrasonic probes are fixed on the ultrasonic probe frame.

[0027] Furthermore, the ultrasound probe holder is worn on the user's head, and the detection ranges of the two ultrasound probes correspond to the left side and the right side of the user's head respectively.

[0028] Furthermore, the non-invasive ultrasound cerebral hemorrhage treatment device is configured as follows:

[0029] Set the type of ultrasound probe.

[0030] Furthermore, the artificial intelligence module includes:

[0031] A voice information recognition device, used to determine the first symptom information according to the voice information;

[0032] A text information recognition device, used to determine the second symptom information according to the text information; and

[0033] An image information recognition device is used to determine third symptom information based on brain tissue images and cerebral blood vessel images, and

[0034] Based on a preset artificial intelligence model, the artificial intelligence module identifies lesion information according to the first symptom information, the second symptom information and the third symptom information.

[0035] Furthermore, the telemedicine module includes:

[0036] Computer for running the telemedicine module;

[0037] A zoom camera to provide visual information;

[0038] A microphone, used to capture voice information;

[0039] A speaker, for receiving a voice signal; and

[0040] High-speed network card for data transmission.

[0041] Compared with the prior art, this application can at least achieve the following technical effects:

[0042] The present application can be effectively connected with the existing medical imaging system through the image transmission module to ensure the smoothness and reliability of the entire system; then the location of the hematoma can be automatically identified based on the brain tissue image and the cerebral blood vessel image, and the ultrasound irradiation path can be accurately formulated; then the ultrasound equipment is selected and the equipment parameters are set according to the hematoma to ensure the safety of the medical operation; then the status data of the brain tissue and cerebral blood vessels are obtained in a timely manner through the ultrasound monitoring equipment, and real-time feedback is provided to the doctor during the treatment process, which helps to adjust the treatment plan in time to ensure the safety of the patient and the treatment effect; the intelligent decision-making support module integrates a variety of information and data to provide doctors with personalized and precise ultrasound irradiation plans, promote the rate and efficiency of hematoma absorption, and reduce the disability and mortality rates of cerebral hemorrhage. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate one or more embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0044] Figure 1 A schematic diagram of the structure of a non-invasive ultrasound-based cerebral hemorrhage treatment device provided in one or more embodiments of this specification;

[0045] Figure 2 A schematic diagram of the structure of a non-invasive ultrasound-based cerebral hemorrhage treatment system provided in one or more embodiments of this specification;

[0046] Figure 3A flow chart of a non-invasive ultrasound-based treatment method for cerebral hemorrhage provided for one or more embodiments of this specification. DETAILED DESCRIPTION

[0047] In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the following will be combined with the drawings in one or more embodiments of this specification to clearly and completely describe the technical solutions in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this document.

[0048] The existing technology for patients with cerebral hemorrhage mainly uses minimally invasive treatment, but since minimally invasive treatment will leave wounds, the presence of wounds affects the patient's treatment time, treatment effect and physical health.

[0049] In order to solve the above technical problems, the present application proposes a non-invasive ultrasound-based cerebral hemorrhage treatment device, such as Figure 1 As shown, specifically including:

[0050] In the embodiment of the present application, the image transmission module 101 is used to obtain brain tissue images and cerebrovascular images; the intelligent hematoma positioning module 102 is used to determine the location information of the hematoma based on the brain tissue images and the cerebrovascular images; the ultrasound irradiation path is determined based on the location information of the hematoma, the brain tissue images and the cerebrovascular images; the ultrasound intervention module 103 is used to set the parameters of the ultrasound device; the ultrasound monitoring module 104 is used to obtain the status data of the hematoma site of cerebral hemorrhage, the edema site around the hematoma, the intracranial pressure, the optic nerve sheath and the deep vein thrombosis; the intelligent auxiliary decision module 105 is used to determine the ultrasound irradiation plan based on the ultrasound irradiation path, the parameters of the ultrasound device and the status data.

[0051] Specifically, the image transmission module is connected to the medical imaging workstation to facilitate the acquisition of brain tissue images and cerebrovascular images. The intelligent hematoma positioning module uses artificial intelligence to identify brain tissue images and cerebrovascular images, determine the location of lesions in the brain and plan the best path for ultrasound irradiation. The ultrasound intervention module sets and adjusts the parameters of the ultrasound intervention device to ensure that the ultrasound intervention device can play the best effect when acute ultrasound irradiation is performed to promote hematoma absorption, reduce damage to brain tissue and improve surgical results. The ultrasound monitoring module uses ultrasound monitoring technology to determine the location, size and other status data of hematomas in brain tissue and cerebral blood vessels to ensure the safety of the operation. The intelligent decision-making assistance module formulates a non-invasive ultrasound cerebral hemorrhage intervention plan that meets the needs of each patient based on the ultrasound irradiation path, the optimal parameters of the ultrasound equipment and the status information of various parts of the brain, promotes the absorption rate and efficiency of cerebral hemorrhage hematomas, and reduces the disability and mortality rates of cerebral hemorrhage.

[0052] For example: Image transmission module: The computed tomography (CT) in the medical imaging workstation uses an X-ray beam to scan the brain, and obtains brain tissue images after computer processing, or the nuclear magnetic resonance (MR) in the medical imaging workstation uses the signals generated by the nucleus in the magnetic field to reconstruct the cerebrovascular image. High-quality image data is the basis for subsequent analysis and diagnosis. The image transmission module obtains data from the medical imaging workstation to ensure the accuracy and real-time nature of the data, which is crucial to improving diagnostic efficiency and accuracy. Intelligent hematoma positioning module: Using advanced image processing technology and algorithms, comprehensive analysis of brain tissue images and cerebrovascular images is performed to automatically identify and locate the location of hematomas in the brain. Accurate positioning of hematomas is a prerequisite for formulating an effective treatment plan, which helps reduce surgical risks and improve treatment effects. Ultrasound intervention module: According to the location of the hematoma and the specific conditions of the patient, the parameters of the ultrasound equipment, such as frequency, intensity, irradiation time, etc., are set to prepare for subsequent ultrasound treatment. Reasonable ultrasound parameter settings are the key to ensuring treatment effectiveness and safety. Ultrasound monitoring module: Before and during treatment, the status data of brain tissue and cerebral blood vessels, such as blood flow velocity, are obtained in real time. By monitoring this data, the ultrasound parameters can be adjusted in time to avoid unnecessary damage to surrounding tissues and evaluate the treatment effect. Intelligent decision-making support module: The optimal ultrasound irradiation plan is generated through complex algorithms and models based on the comprehensive ultrasound irradiation path, ultrasound equipment parameters and monitored status data, ensuring the personalization and accuracy of the treatment plan, helping to improve the success rate of treatment and reduce complications.

[0053] The entire system is highly integrated and intelligent, achieving full-process management from image acquisition, hematoma positioning, ultrasound intervention to effect monitoring. This system not only improves the efficiency and quality of medical services, but also reduces the workload of medical staff and provides patients with safer and more effective treatment options.

[0054] In an embodiment of the present application, the image transmission module is configured to obtain the brain tissue image and the cerebral blood vessel image from an imaging workstation via a wired network or a wireless network.

[0055] Specifically, after obtaining brain tissue images and cerebrovascular images using a medical imaging workstation, the brain tissue images and cerebrovascular images are transmitted using a network, wherein the network transmission mode includes: wired network connection and wireless network connection. For example: the wired network connection is a network cable connection, and the wireless network connection is a wifi or Bluetooth connection.

[0056] In the embodiment of the present application, the intelligent hematoma positioning module is configured as follows:

[0057] According to the brain tissue image and the cerebral blood vessel image, the tissue space information around the hematoma is determined; according to the location information of the hematoma and the tissue space information, the ultrasound irradiation path is determined.

[0058] Specifically, based on brain tissue images and cerebral vascular images, the tissue space information around the hematoma is identified, including data such as the tissue location, volume size, density characteristics, morphological characteristics, and the distance of the hematoma from the cortex. Then, based on the location information and tissue space information of the hematoma, the ultrasound irradiation path is given, including the optimal irradiation angle and distance. In addition, parameters such as the energy, frequency, and intensity of the ultrasound are recommended. When planning the path, it is possible to avoid important brain tissues and cerebral blood vessels and formulate a precise puncture path, thereby finding an ultrasound irradiation path that has the least impact on the human body, to ensure the safety of non-invasive ultrasound treatment.

[0059] In the embodiment of the present application, the ultrasound intervention module is configured to: set the ultrasound intervention frequency and the ultrasound intervention time.

[0060] Specifically, since different ultrasound intervention probes need to be selected for different lesion locations, the intervention frequency and intervention time need to be considered for different ultrasound intervention probes, where the ultrasound intervention frequency refers to the number of times the ultrasound wave vibrates per unit time, usually expressed in Hertz (Hz). Ultrasound waves of different frequencies have different penetration, attenuation characteristics and therapeutic effects in human tissues. Selecting the right ultrasound frequency can ensure that the ultrasound wave can penetrate to the target depth and generate enough energy in the target area to produce a therapeutic effect. At the same time, avoid excessive frequency causing excessive concentration of energy in the superficial layer, causing unnecessary damage. The ultrasound intervention time refers to the time that the ultrasound wave continues to act in the treatment area. This time length needs to be comprehensively determined based on the patient's specific situation, the purpose of treatment and the performance of the ultrasound equipment. Too short an intervention time may not achieve the expected therapeutic effect, while too long an intervention time may increase the patient's discomfort and potential risks. Therefore, it is crucial to reasonably set the ultrasound intervention time to ensure the safety and effectiveness of treatment.

[0061] For example: Based on the patient's head size, cerebral cortex thickness, skull thickness, and hematoma location, the doctor selected a suitable high-frequency focused ultrasound probe. The doctor can adjust the ultrasound intervention frequency (such as between 2MHz and 16MHz). This frequency range can not only penetrate the skull and brain tissue, but also generate sufficient energy in the hematoma area to promote the liquefaction and discharge of the hematoma. At the same time, considering avoiding unnecessary damage to surrounding tissues, the doctor selected a moderate value within the frequency range. Based on the patient's specific situation and the performance of the ultrasound equipment, the doctor set the time for each ultrasound intervention to 30 minutes. This time length is based on previous clinical experience and research data, and is intended to ensure sufficient energy transfer to produce a therapeutic effect while avoiding the discomfort and risks that may be caused by long-term exposure of patients to ultrasound.

[0062] In an embodiment of the present application, the ultrasound monitoring module is configured to: monitor the status of the hematoma site of cerebral hemorrhage, the edema site around the hematoma, the intracranial pressure, the optic nerve sheath and the deep vein thrombosis, and obtain the status data.

[0063] For example, monitoring of the hematoma site of cerebral hemorrhage: using transcranial Doppler (TCD) ultrasound, the ultrasound probe is used to scan the brain through the temporal window, occipital window, mandibular window or transorbital window, and observe the high echo area of ​​the hematoma. Monitoring of edema around the hematoma: using TCD ultrasound to observe the low echo or no echo area around the hematoma, which usually indicates edema. By measuring the area and thickness of the edema area, the severity of the edema is assessed. Monitoring of intracranial pressure: using optic nerve sheath ultrasound (ONS) for non-invasive intracranial pressure monitoring. By measuring the diameter of the optic nerve sheath, the changes in intracranial pressure are assessed. Monitoring of the optic nerve sheath: using the ONS method, the diameter of the optic nerve sheath is directly measured, and the morphology, thickness and echo characteristics of the optic nerve sheath are observed to assess whether it is affected by increased intracranial pressure or other lesions. Monitoring of deep vein thrombosis: using Doppler ultrasound to monitor deep vein thrombosis, the blood state is observed through the Doppler effect, such as blood flow velocity, blood clot formation, vascular intimal rupture, etc., and the presence of thrombus and its location and size are observed.

[0064] Ultrasound monitoring does not require puncture or injection of contrast agents for patients and is a completely non-invasive examination method. It reduces the pain and discomfort of patients and avoids complications that may be caused by trauma. In addition, ultrasound can display the dynamic changes of tissue structure and blood flow in real time, allowing doctors to immediately observe the condition of lesions. This is especially important for emergency situations where rapid diagnosis and treatment decisions need to be made. That is, this application achieves synchronization of monitoring and treatment based on ultrasound technology, thereby ensuring the treatment effect.

[0065] The embodiment of the present application provides a non-invasive ultrasonic cerebral hemorrhage treatment system, including an artificial intelligence module, a telemedicine module, a cloud platform management module, a power module, and a non-invasive ultrasonic cerebral hemorrhage treatment device as described in any one of the above embodiments, such as Figure 2 shown.

[0066] In an embodiment of the present application, an artificial intelligence module is used to identify lesion information.

[0067] Specifically, first, a large amount of brain tissue images (such as magnetic resonance imaging (MRI), CT), cerebrovascular images (such as CT angiography (CTA), magnetic resonance angiography (MRA)), and voice information describing the patient's condition and text information data in the case are collected. These data should contain the annotation information of known lesions for model training and verification. Secondly, the collected image data is preprocessed, including denoising, normalization, segmentation and other steps to improve the quality and consistency of the data. At the same time, the lesions are accurately labeled to ensure that the model can learn the characteristics of the lesions. Thirdly, according to the specific needs of lesion identification, a suitable deep learning model is selected. For example: convolutional neural network (CNN), U-Net, Fast R-CNN (Region-based Convolutional Network, region-based convolutional neural network), etc. Finally, the trained artificial intelligence model is applied to new brain tissue images and cerebrovascular images to automatically identify information such as the location, size and morphology of the lesions.

[0068] For example: the patient's description of the condition, medical records, and brain tissue and cerebral vascular images obtained through ultrasound technology are input into a trained artificial intelligence model to identify lesion information.

[0069] In an embodiment of the present application, the telemedicine module is used to determine an ultrasound irradiation plan based on remote guidance.

[0070] Specifically, doctors at primary medical centers can transmit patients' clinical information (including cranial CT / MRI scan results, CTA / MRA scan results, coagulation and biochemical test results, neurological and internal medicine physical examination results, etc.) to doctors at advanced medical centers; doctors at advanced medical centers evaluate patients' clinical information, determine whether patients are suitable for radiation therapy and the specific radiation plan, and provide feedback to doctors at primary medical centers through telemedicine. Doctors at primary medical centers can implement ultrasound radiation plans under the supervision and guidance of doctors at advanced medical centers; doctors at advanced medical centers can also implement remote treatment through telemedicine with the cooperation of doctors at primary medical centers. During and after surgical treatment, doctors at advanced medical centers can monitor changes in patients' level of consciousness, focal neurological dysfunction, blood pressure, heart rate, respiration, blood oxygen, etc. in real time through telemedicine.

[0071] In an embodiment of the present application, a power module is used to supply power to the system.

[0072] Specifically, the power module, as the core component of the system power supply, can convert the input power (such as AC or DC) into the power form required by the device to ensure the normal operation of the device. In addition to the basic power conversion function, the power module also has power management functions such as voltage regulation, current limiting, overvoltage protection, and overcurrent protection to ensure the stability and safety of the system.

[0073] In an embodiment of the present application, the cloud platform management module is used to connect the artificial intelligence module, the non-invasive ultrasound cerebral hemorrhage treatment device, the telemedicine module and the power module.

[0074] Specifically, the cloud platform management module is responsible for coordinating the communication, data processing, task scheduling and fault monitoring among various components to ensure the efficient, safe and stable operation of the entire system. Through efficient and intelligent management methods, it provides strong technical support and guarantee for application scenarios such as non-invasive cerebral hemorrhage treatment and telemedicine.

[0075] Furthermore, in an embodiment of the present application, the system includes: an ultrasound probe fixing frame, including two ultrasound probes and an ultrasound head frame, and the two ultrasound probes are fixed on the ultrasound probe frame.

[0076] Specifically, the two ultrasound probes and the ultrasound head frame are fixed by the ultrasound probe fixing frame so that they do not shift during the medical operation, thereby facilitating the doctor's operation. The ultrasound probe fixing frame provides important support and guarantee for medical operations by providing stable probe support and flexible angle adjustment functions. Preferably, the ultrasound probe frame is worn on the user's head, and the detection ranges of the two ultrasound probes correspond to the left and right sides of the user's head, respectively, to ensure that monitoring and treatment can be completed from as many angles as possible.

[0077] Furthermore, in the implementation of the present application, the non-invasive ultrasonic cerebral hemorrhage treatment device is configured to: set the type of ultrasonic probe.

[0078] Specifically, since different lesion locations require the selection of corresponding ultrasound intervention probes to ensure the accuracy and efficiency of detection, the selection of probes depends on the specific needs of the treatment, such as selecting probes of different frequencies.

[0079] Furthermore, in the embodiment of the present application, the artificial intelligence module includes:

[0080] A voice information recognition device is used to determine the first symptom information based on the voice information; a text information recognition device is used to determine the second symptom information based on the text information; an image information recognition device is used to determine the third symptom information based on the brain tissue image and the cerebral blood vessel image; based on a preset artificial intelligence model, the artificial intelligence module identifies the lesion information based on the first symptom information, the second symptom information and the third symptom information.

[0081] Specifically, the voice information recognition device uses advanced voice recognition technology to convert the patient's verbal description of the disease information (such as symptoms, pain, medical history, etc.) into processable text data. For example: using natural language processing (NLP) technology to understand and analyze the patient's voice content, extract key information, and determine the first symptom information. Voice information recognition provides patients with a convenient way to input information, especially for patients with limited mobility or vision. At the same time, it also helps medical staff quickly obtain the patient's preliminary condition information and provide support for subsequent diagnosis and treatment.

[0082] Text information recognition equipment recognizes and analyzes text information such as case reports and diagnostic records written by doctors for patients. For example, optical character recognition (OCR) technology is used to convert handwritten or printed text into editable electronic text, and NLP technology is used to extract key information in the case, such as diagnosis results, treatment plans, medication records, etc., to determine secondary symptom information. Text information recognition helps to achieve digital management of cases and improve the accessibility and analyzability of medical information. At the same time, it also supports the integration and sharing of medical data, providing rich data resources for clinical decision-making, medical research, etc.

[0083] Image information recognition equipment conducts in-depth analysis of brain tissue images and cerebral vascular images obtained by ultrasound imaging technology. For example, advanced algorithms such as deep learning are used to automatically identify abnormal areas such as hematomas, tumors, and infarctions in images to determine third-party symptom information. Through automatic recognition and analysis of ultrasound images, doctors can find lesions more quickly and accurately.

[0084] Finally, voice, text and image information are combined for multimodal fusion analysis to identify lesion information; the artificial intelligence module can integrate data from different information sources and conduct comprehensive analysis through complex algorithms and models. This multimodal fusion analysis can make full use of the advantages of various data, improve the accuracy and reliability of lesion identification, and thus improve the quality and efficiency of medical services.

[0085] Furthermore, in an embodiment of the present application, the telemedicine module includes: a computer for running the telemedicine module; a zoom camera for providing visual information; a microphone for capturing voice information; a speaker for receiving voice signals; and a high-speed network card for realizing data transmission.

[0086] Specifically, the computer, as the core processing unit of the entire system, is responsible for running telemedicine software, processing image and sound data, storing patient information, and providing a user interface for medical staff to operate. Modern telemedicine systems often use high-performance computers or dedicated servers to ensure rapid data processing and transmission. The zoom camera can clearly capture the patient's facial expressions, physical condition, and medical operation details, providing doctors with intuitive visual information. The zoom function allows the camera to adjust the field of view as needed to better meet the needs of diagnosis or treatment. In remote surgery, high-definition zoom cameras are particularly important and can provide precise surgical fields of view. Microphones are used to capture the voices of patients and medical staff to achieve real-time communication between the two parties. High-quality microphones can ensure the clarity and accuracy of voice transmission, reduce noise interference, and improve the effectiveness of telemedicine consultation or treatment. The speaker is responsible for converting the received voice signal into audible sound, so that the patient can clearly hear the instructions or suggestions of the medical staff; during the telemedicine consultation process, the sound quality of the speaker directly affects the smoothness of communication. High-speed network cards realize data transmission. It is responsible for quickly and stably transmitting the video captured by the camera, the audio collected by the microphone, and the data processed by the computer to the remote server or receiving end. High-speed and stable network connection is the basis for the normal operation of the telemedicine system. High-speed network cards ensure real-time transmission of video and audio, reduce delays and freezes, and improve the efficiency and quality of telemedicine services.

[0087] In the embodiments of the present application, the present application proposes a non-invasive ultrasound-based treatment method for cerebral hemorrhage, such as Figure 3 As shown, the following steps are included:

[0088] Step S1, acquiring brain tissue images and cerebral blood vessel images.

[0089] In the embodiments of the present application, brain tissue images are obtained by CT or MRI, and cerebral vascular images are obtained by CTA or MRA.

[0090] Step S2, determining the location information of the hematoma according to the brain tissue image and the cerebral blood vessel image.

[0091] Step S3, determining the ultrasound irradiation path according to the location information of the hematoma, the brain tissue image and the cerebral blood vessel image.

[0092] In the embodiments of the present application, brain tissue images are used to determine the exact location, morphology and relationship of the target brain tissue with surrounding structures, wherein the target brain tissue is a lesion area, such as a bleeding site. Cerebrovascular images are used to observe the course, branches and lesions of cerebral blood vessels, determine the target blood vessels and their relationship with surrounding blood vessels, identify possible stenosis and other lesions, and use TCD to detect parameters such as blood flow velocity and blood flow direction of the target blood vessels, providing a functional basis for the selection of ultrasound irradiation paths. Based on the comprehensive information of brain tissue images and cerebral vascular images, a safe and effective ultrasound irradiation path is planned.

[0093] Step S4, setting parameters of the ultrasound equipment.

[0094] In an embodiment of the present application, after the ultrasound irradiation path is formulated, the corresponding ultrasound probe is selected according to the patient's lesion location, and parameters such as the frequency and intervention time of the ultrasound intervention device are set to ensure that the parameter settings can enable the ultrasound to maintain sufficient energy and focusing effect when penetrating the brain tissue, while avoiding unnecessary damage to surrounding tissues and blood vessels.

[0095] Step S5, obtaining the status data of the hematoma site of cerebral hemorrhage, the degree of edema around the hematoma, the intracranial pressure, the optic nerve sheath and the deep vein thrombosis.

[0096] In the embodiment of the present application, the brain hemorrhage hematoma location state data and the edema degree state data around the hematoma are used to characterize whether the hematoma is getting bigger or smaller. The intracranial pressure state data are used to characterize whether the intracranial pressure is increased. The optic nerve sheath state data are used to characterize whether the optic nerve sheath is enlarged. The deep vein thrombosis state data are used to characterize whether deep vein thrombosis occurs.

[0097] Step S6, determining an ultrasound irradiation plan according to the ultrasound irradiation path, the parameters of the ultrasound device and the status data.

[0098] In the embodiment of the present application, the ultrasound irradiation path, ultrasound equipment parameters and brain tissue / cerebral blood vessel status data are comprehensively analyzed to formulate a detailed ultrasound irradiation plan. The ultrasound irradiation plan includes specific parameters such as the starting position, direction, speed, duration of ultrasound irradiation, as well as possible adjustment measures and response strategies to ensure that the plan can safely and effectively achieve the treatment goals while minimizing damage to surrounding tissues and side effects.

[0099] Furthermore, in an embodiment of the present application, lesion data is determined based on the brain tissue image and the cerebral blood vessel image; ultrasound parameters are determined based on the lesion data based on transcranial Doppler ultrasound; and the ultrasound irradiation path is determined based on the lesion data and the ultrasound parameters.

[0100] Specifically, the specific location, size, morphology and relationship of the lesion with the surrounding tissue are identified and determined through brain tissue imaging and cerebral vascular imaging. The severity of the lesion, the speed of development and the impact on the patient's quality of life are evaluated to provide a basis for formulating a treatment plan. TCD technology is used to detect hemodynamic parameters such as blood flow velocity, blood flow direction, pulsatility index, and possible blood flow abnormalities (such as stenosis, eddy current, etc.) in the target vascular area. According to the TCD test results and lesion data (such as lesion location, size, morphology, etc.), the parameters of the ultrasound equipment are set. Among them, the parameters include ultrasound frequency, power, pulse width, focal depth, irradiation time, etc., which are intended to ensure that the ultrasound can accurately reach the lesion area and produce the expected therapeutic effect. Combined with lesion data and ultrasound parameters, a safe and effective ultrasound irradiation path is planned. This path should avoid important neural structures and blood vessels as much as possible to ensure that the ultrasound can reach the lesion area smoothly.

[0101] Furthermore, in an embodiment of the present application, the status of the hematoma site of cerebral hemorrhage, the degree of edema around the hematoma, the intracranial pressure, the optic nerve sheath, deep vein thrombosis and other organs is monitored, and the status data is obtained.

[0102] Ultrasound monitoring is used to monitor the location of cerebral hematoma, the degree of edema around the hematoma, intracranial pressure, optic nerve sheath and deep vein thrombosis, so that the treatment plan can be adjusted in time to improve the treatment effect.

[0103] An embodiment of the present application provides a storage medium for storing computer-executable instructions, which, when executed, implement the steps of the non-invasive ultrasound-based cerebral hemorrhage treatment method described in any one of the above embodiments.

[0104] It should be noted that the embodiments of the storage medium in this specification and the embodiments of the blockchain-based service provision method in this specification are based on the same inventive concept. Therefore, the specific implementation of this embodiment can refer to the aforementioned corresponding implementation of the blockchain-based service provision method, and the repeated parts will not be repeated.

[0105] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0106] In the 1930s, improvements to a technology could be clearly distinguished as hardware improvements (for example, improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the method flow). However, with the development of technology, many improvements to the method flow today can be regarded as direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that an improvement in a method flow cannot be implemented using a hardware entity module. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to ask a chip manufacturer to design and produce a dedicated integrated circuit chip. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.

[0107] The controller can be implemented in any appropriate manner, for example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (such as software or firmware) that can be executed by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art also know that in addition to implementing the controller in a purely computer-readable program code manner, the controller can be implemented in the form of a logic gate, a switch, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, this controller can be considered as a hardware component, and the devices included therein for implementing various functions can also be regarded as structures within the hardware component. Or even, the devices for implementing various functions can be regarded as both software modules for implementing the method and structures within the hardware component.

[0108] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0109] For the convenience of description, the above devices are described in terms of functions and are divided into various units. Of course, when implementing the embodiments of this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0110] It should be understood by those skilled in the art that one or more embodiments of this specification may be provided as a method, system or computer program product. Therefore, one or more embodiments of this specification may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0111] This specification is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0112] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0113] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0114] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0115] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0116] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0117] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0118] One or more embodiments of the present specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. One or more embodiments of the present specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0119] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0120] The above description is only an embodiment of this document and is not intended to limit this document. For those skilled in the art, this document may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this document should be included in the scope of the claims of this document.

Claims

1. A non-invasive ultrasound-based cerebral hemorrhage treatment device, characterized in that include: An image transmission module, used to obtain brain tissue images and cerebral blood vessel images; An intelligent hematoma positioning module, used to determine the location information of the hematoma according to the brain tissue image and the cerebral blood vessel image; and determine the ultrasound irradiation path according to the location information of the hematoma, the brain tissue image and the cerebral blood vessel image; Ultrasound intervention module, used to set the parameters of the ultrasound equipment; Ultrasound monitoring module, used to obtain data on the location of cerebral hemorrhage and hematoma, degree of edema around the hematoma, intracranial pressure, optic nerve sheath and status of deep vein thrombosis; and The intelligent auxiliary decision-making module is used to determine the ultrasound irradiation plan according to the ultrasound irradiation path, the parameters of the ultrasound equipment and the status data.

2. The device according to claim 1, characterized in that The image transmission module is configured as follows: The brain tissue image and the cerebral blood vessel image are acquired from an imaging workstation via a wired network or a wireless network.

3. The device according to claim 1, characterized in that The intelligent hematoma positioning module is configured as follows: Determining tissue space information around the hematoma according to the brain tissue image and the cerebral blood vessel image; and The ultrasound irradiation path is determined based on the location information of the hematoma and the tissue space information.

4. The device according to claim 1, characterized in that The ultrasound intervention module is configured to: Set the ultrasound intervention frequency and ultrasound intervention time.

5. A non-invasive ultrasound system for treating cerebral hemorrhage, characterized in that include: The non-invasive ultrasound-based cerebral hemorrhage treatment device according to any one of claims 1 to 4; Artificial intelligence module, used to identify lesion information; A telemedicine module, used for determining an ultrasound irradiation plan according to remote guidance; A power module, used to supply power to the system; as well as A cloud platform management module is used to connect the artificial intelligence module, the non-invasive ultrasonic cerebral hemorrhage treatment device, the telemedicine module and the power module.

6. The system according to claim 5, characterized in that The system comprises: The ultrasonic probe fixing frame comprises two ultrasonic probes and an ultrasonic head frame, and the two ultrasonic probes are fixed on the ultrasonic probe frame.

7. The system according to claim 6, characterized in that The ultrasonic probe holder is worn on the user's head, and the detection ranges of the two ultrasonic probes correspond to the left hemisphere and the right hemisphere of the user's head respectively.

8. The system according to claim 5, characterized in that The non-invasive ultrasonic cerebral hemorrhage treatment device is configured as follows: Set the type of ultrasound probe.

9. The system according to claim 5, characterized in that Artificial intelligence modules include: A voice information recognition device, used to determine the first symptom information according to the voice information; A text information recognition device, used to determine the second symptom information according to the text information; and An image information recognition device is used to determine third symptom information based on brain tissue images and cerebral blood vessel images, and Based on a preset artificial intelligence model, the artificial intelligence module identifies lesion information according to the first symptom information, the second symptom information and the third symptom information.

10. The system according to claim 5, characterized in that remote The medical module includes: Computer for running the telemedicine module; A zoom camera to provide visual information; A microphone, used to capture voice information; A speaker, for receiving a voice signal; and High-speed network card for data transmission.

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