CN111037584A - Medical image robot and control method thereof - Google Patents
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- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
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- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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Abstract
The invention discloses a medical imaging robot, comprising: the system comprises a cloud service platform, a basic service end and an expert service end; the cloud service platform is provided with an information management system; the cloud service platform, the basic level server and the expert server are connected through a network transmission channel, and the cloud service platform comprises a data storage module, a data analysis module and a report generation module; the information management system adopts a layered architecture and comprises an application interaction layer and a block chain layer; through intelligent control, an expert server is added, medical guarantee is enhanced, and medical accidents are reduced; the medical image data is transmitted at high speed in the IPv6 network environment, and the transmission performance is stable; through the layered processing mode, the data acquisition safety and the storage safety are realized, and the system has strong safety and practicability.
Description
Technical Field
The invention belongs to the technical field of medical imaging, and particularly relates to a medical imaging robot and a control method thereof.
Background
Medical imaging refers to the technique and process of obtaining internal tissue images of a human body or a part of a human body in a non-invasive manner for medical treatment or medical research; with the gradual deployment of various image acquisition equipment in basic level medical institutions, more and more basic level patients can carry out medical image acquisition according to clinical requirements. Since the diagnosis of medical images mainly depends on the professional skills and personal experiences of medical staff, the related skill level of basic medical staff is insufficient, and missed diagnosis and misdiagnosis are more prominent.
Most of medical imaging robots in the current market work singly, only can simply shoot and collect data and image data, and the intelligence is far from enough, and especially in remote areas and areas with underdeveloped medical treatment, the medical imaging robots lack of experts to see a doctor, are difficult to take medicines according to the symptoms, and are easy to cause the situation of delayed treatment; in addition, the medical image data volume is large, the medical data transmission speed is slow due to the limitation of the network transmission rate, and the timeliness of clinical diagnosis work is influenced; the current image robot system is not strong enough, once a server crashes, the whole system can not operate, and normal use is influenced; when the central database is attacked by the outside or the data is maliciously modified by the manager, the authenticity of the data is damaged, and serious medical accidents are caused.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a medical imaging robot and a control method thereof, which solve the problems in the background technology, increase expert service terminals through intelligent control, strengthen medical guarantee and reduce medical accidents; the medical image data is transmitted at high speed in the IPv6 network environment, and the transmission performance is stable; through the layered processing mode, the data acquisition safety and the storage safety are realized, and the system has strong safety and practicability.
The invention provides the following technical scheme:
a medical imaging robot, comprising: the system comprises a cloud service platform, a basic service end and an expert service end; the cloud service platform is provided with an information management system; the cloud service platform, the basic level server and the expert server are connected through a network transmission channel, and the cloud service platform comprises a data storage module, a data analysis module and a report generation module; the information management system adopts a layered architecture and comprises an application interaction layer and a block chain layer.
Preferably, the base-level server comprises a report query module, a data acquisition module and a case discussion module; the expert server comprises a case viewing module, a report auditing module and a case discussion module.
Preferably, the robot adopts a layered processing mode to carry out system construction, and comprises a data layer, a network layer, an interface layer, a storage layer, a processing layer and an application layer.
Preferably, the data layer is used for collecting medical image data information, the network layer is used for transmitting information, the interface layer adopts multi-source heterogeneous data processing, the storage layer stores the data information, the processing layer performs data processing and generates reports, and the application layer comprises an information management system, a basic service end and an expert service end.
Preferably, the structured data is stored by using a data warehouse, and the unstructured data adopts a Hadoop distributed storage structure.
Preferably, the interaction layer uses a Web terminal interface for interaction; one part of the blockchain layer is a P2P network that maintains the functions of the system to run and process queries and stores, and the other part is used for blockchain storage of record chains that have been validated.
Preferably, an application layer on the upper layer of the information management system displays various operation buttons through a terminal Web interface, data exchange between a user and a block chain is completed through the operation buttons, the block chain encapsulates image data information submitted by a basic service end into virtual assets or transactions, the virtual assets or transactions are submitted to various nodes for verification and storage on the block chain, meanwhile, the application layer also provides an inquiry function for an expert service end, and data are obtained through the inquiry function and displayed on the Web interface.
The process of packaging the information into virtual assets or transactions is as follows: after data are collected, the data are signed and then stored in an IPFS (internet protocol file system), the IPFS returns a stored data index hash, the index hash is encrypted by a system public key and then stored in a block chain, the IPFS can perform decentralized distributed storage on a large amount of data, the data from a data processing module of a central server of a practical training platform are received in the system and stored on a node of the IPFS, and then data calling of an application layer is received; the data acquisition safety and the storage safety are realized, and the safety is strong.
Preferably, the network transmission channel is an ipv6 high-speed transmission channel.
Preferably, a network environment needs to be configured by adopting an ipv6 high-speed transmission channel, and the application layer comprises a network communication interface (HTTP interface, Wed Service interface, Socket communication) programming or interface upgrading support ipv 6; applications and bare computers support ipv 6; the data layer comprises configuration and storage support ipv6 of IP addresses in the database; network access provides dual stack access supporting ipv 6.
Preferably, a method for controlling a medical imaging robot includes the steps of:
s1: the basic-level server is responsible for acquiring medical image data, the acquired image data is uploaded to a cloud service platform through an IPv6 high-speed channel and is stored in time, data analysis is carried out through the cloud service platform, and a diagnosis report is obtained preliminarily;
s2: after step S1, the generated diagnosis report is pushed to the expert server, the diagnosis report is referred to by viewing the medical image and the expert diagnosis, the final diagnosis is made, and the diagnosis report is transmitted to the cloud service platform;
s3: and downloading an expert diagnosis report by the basic service terminal to confirm diagnosis.
Preferably, in step S1, the data analysis uses a method of computer image omics to extract a large number of three major features including first-order statistical features, spatial geometric features, and texture features, and after feature dimension reduction, model establishment is performed on dimension-reduced data; the first-order statistical features are 16 (mainly scalar quantity for describing brightness), the space geometric features are 9 (mainly scalar quantity for describing space geometric characteristics), and the texture features are 300 (mainly scalar quantity for describing internal features of the focus); and (3) grouping the extracted various features by using a mutual information method, calculating information gain in each group, selecting the feature with the maximum gain to construct a dimension reduction candidate set, finally performing model training, generating a classification model, importing the classification model for classification, and finally outputting an analysis result.
Preferably, in order to improve the accuracy of information processing and prevent external interference on data information, so as to increase the safety of data transmission of the medical imaging robot, the ipv6 high-speed transmission channels are all connected by shielded wires.
Preferably, the shielding wire is a multilayer shielding wire, a plurality of strands of metal wires of the wire core of the shielding wire are twisted with each other, a first insulating layer is arranged on the outer side of the shielding wire, and the twisted plurality of strands of metal wires are tightly wrapped together by the first insulating layer; the first insulating layer outside is provided with first shielding layer, the first shielding layer outside is provided with the second insulating layer, the second insulating layer outside is provided with the second shielding layer, the second shielding layer outside is provided with the third insulating layer.
Preferably, the wire core is made of copper; the first shielding layer and the second shielding layer are made of conductive cloth, woven copper mesh or copper (aluminum) platinum.
Preferably, in order to increase the toughness and the endurance of the shielded wire, the number of strands of the copper wire core is n, the diameter of each strand of the copper wire core is r, and the diameter of the shielded wire is d, so that d satisfies the following relation:
d=α·n/πr。
in the above formula, α is a relation factor, the value range is 0.25=3.68, and the unit of r and d is mm.
Preferably, when the electric current passes through the signal line, because the sinle silk has stranded copper line to twist each other to form, can produce mutual inductance l when transmitting, the production of heat, in order to increase the security of transmission, reduces thermal production, better prevention signal interference, mutual inductance l satisfies following relation:
l=β·μ0/nπ·ln（d/nr）；
wherein, mu 0 is magnetic conductivity in vacuum, l unit is mH, β is coefficient, and the value range is 0.06-0.14.
Compared with the prior art, the invention has the following beneficial effects:
(1) according to the medical imaging robot and the control method thereof, through intelligent control, an expert server is added, medical guarantee is enhanced, and medical accidents are reduced; the network layer adopts an IPv6 protocol to realize the rapid forwarding of medical big data, improve the safety of data transmission and reduce the phenomena of jitter and packet loss in the transmission process.
(2) According to the medical image robot and the control method thereof, data acquisition safety and storage safety are realized in a layered processing mode, and the robot has strong safety and practicability.
(3) The invention relates to a medical image robot and a control method thereof.A data warehouse is used for storing structured data, and a Hadoop distributed storage structure is adopted for unstructured data; the privacy of the patient is fully protected, and medical data are processed by using a privacy removing technology.
(4) According to the medical imaging robot and the control method thereof, the relation among n, r and d is limited, when current passes through a signal wire, the wire core is formed by twisting a plurality of strands of copper wires, so that the transmission safety is improved, the generation of heat is reduced, and the signal interference is better prevented.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a functional schematic of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be described in detail and completely with reference to the accompanying drawings. It is to be understood that the described embodiments are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
The first embodiment is as follows:
referring to fig. 1, a medical imaging robot includes: the system comprises a cloud service platform, a basic service end and an expert service end; the cloud service platform is provided with an information management system; the cloud service platform, the basic level server and the expert server are connected through a network transmission channel, and the cloud service platform comprises a data storage module, a data analysis module and a report generation module; the information management system adopts a layered architecture and comprises an application interaction layer and a block chain layer.
The basic-level server comprises a report query module, a data acquisition module and a case discussion module; the expert server comprises a case viewing module, a report auditing module and a case discussion module.
The robot adopts a layered processing mode to carry out system construction and comprises a data layer, a network layer, an interface layer, a storage layer, a processing layer and an application layer.
The medical image data processing system comprises a data layer, a network layer, an interface layer, a storage layer, a processing layer and an application layer, wherein the data layer is used for acquiring medical image data information, the network layer is used for transmitting information, the interface layer adopts multi-source heterogeneous data processing, the storage layer stores the data information, the processing layer performs data processing and generates reports, and the application layer comprises an information management system, a basic server and an expert server.
The structured data are stored by using a data warehouse, and the unstructured data adopt a Hadoop distributed storage structure.
The interaction layer uses a Web terminal interface for interaction; one part of the blockchain layer is a P2P network that maintains the functions of the system to run and process queries and stores, and the other part is used for blockchain storage of record chains that have been validated.
An application layer on the upper layer of the information management system displays various operation buttons through a terminal Web interface, data exchange between a user and a block chain is completed through the operation buttons, the block chain encapsulates image data information submitted by a basic service end into virtual assets or transactions, the virtual assets or transactions are submitted to various nodes to be verified and stored on the block chain, meanwhile, the application layer also provides an inquiry function for an expert service end, and data are obtained through the inquiry function and displayed on the Web interface.
The process of packaging the information into virtual assets or transactions is as follows: after data are collected, the data are signed and then stored in an IPFS (internet protocol file system), the IPFS returns a stored data index hash, the index hash is encrypted by a system public key and then stored in a block chain, the IPFS can perform decentralized distributed storage on a large amount of data, the data from a data processing module of a central server of a practical training platform are received in the system and stored on a node of the IPFS, and then data calling of an application layer is received; the data acquisition safety and the storage safety are realized, and the safety is strong.
The network transmission channel is an ipv6 high-speed transmission channel.
The network environment is required to be configured by adopting an ipv6 high-speed transmission channel, and the application layer comprises a network communication interface (HTTP interface, Wed Service interface and Socket communication) programming or interface upgrading support ipv 6; applications and bare computers support ipv 6; the data layer comprises configuration and storage support ipv6 of IP addresses in the database; network access provides dual stack access supporting ipv 6.
Example two:
the difference from the first embodiment is that a control method of a medical imaging robot includes the following steps:
s1: the basic-level server is responsible for acquiring medical image data, the acquired image data is uploaded to a cloud service platform through an IPv6 high-speed channel and is stored in time, data analysis is carried out through the cloud service platform, and a diagnosis report is obtained preliminarily;
s2: after step S1, the generated diagnosis report is pushed to the expert server, the diagnosis report is referred to by viewing the medical image and the expert diagnosis, the final diagnosis is made, and the diagnosis report is transmitted to the cloud service platform;
s3: and downloading an expert diagnosis report by the basic service terminal to confirm diagnosis.
In step S1, the data analysis uses a computer image omics method to extract a large number of three major features including first-order statistical features, spatial geometric features, and texture features, and after feature dimension reduction, model establishment is performed on dimension-reduced data; the first-order statistical features are 16 (mainly scalar quantity for describing brightness), the space geometric features are 9 (mainly scalar quantity for describing space geometric characteristics), and the texture features are 300 (mainly scalar quantity for describing internal features of the focus); and (3) grouping the extracted various features by using a mutual information method, calculating information gain in each group, selecting the feature with the maximum gain to construct a dimension reduction candidate set, finally performing model training, generating a classification model, importing the classification model for classification, and finally outputting an analysis result.
Example three:
on the basis of the first embodiment and the second embodiment, in order to improve the accuracy of information processing and prevent external interference on data information so as to increase the safety of data transmission of the medical imaging robot, the connection modes for the ipv6 high-speed transmission channel are all connected by adopting a shielded wire.
The shielding wire is a multilayer shielding wire, a plurality of strands of metal wires of a wire core of the shielding wire are twisted with one another, a first insulating layer is arranged on the outer side of the shielding wire, and the twisted plurality of strands of metal wires are tightly wrapped together by the first insulating layer; the first insulating layer outside is provided with first shielding layer, the first shielding layer outside is provided with the second insulating layer, the second insulating layer outside is provided with the second shielding layer, the second shielding layer outside is provided with the third insulating layer.
The wire core is made of copper; the first shielding layer and the second shielding layer are made of conductive cloth, woven copper mesh or copper (aluminum) platinum.
In order to increase the toughness and the endurance of the shielding wire, the number of strands of the copper wire core is n, the diameter of each strand of the copper wire core is r, the diameter of the shielding wire is d, and then d satisfies the following relational expression:
d=α·n/πr。
in the above formula, α is a relation factor, the value range is 0.25=3.68, and the unit of r and d is mm.
Preferably, when the electric current passes through the signal line, because the sinle silk has stranded copper line to twist each other to form, can produce mutual inductance l when transmitting, the production of heat, in order to increase the security of transmission, reduces thermal production, better prevention signal interference, mutual inductance l satisfies following relation:
l=β·μ0/nπ·ln（d/nr）；
wherein, mu 0 is magnetic conductivity in vacuum, l unit is mH, β is coefficient, and the value range is 0.06-0.14.
The device obtained by the technical scheme is a medical imaging robot and a control method thereof, and through intelligent control, an expert server is added, medical guarantee is enhanced, and medical accidents are reduced; the network layer adopts an IPv6 protocol to realize the rapid forwarding of medical big data, improve the safety of data transmission and reduce the phenomena of jitter and packet loss in the transmission process; the data acquisition safety and the storage safety are realized through a layered processing mode, and the system has strong safety and practicability; the structured data are stored by using a data warehouse, and the unstructured data adopt a Hadoop distributed storage structure; the privacy of the patient is fully protected, and medical data are processed by using a privacy removing technology; through restricting the relation between n, r, d, when electric current passes through the signal line, because the sinle silk has stranded copper line to twist each other and forms, increase the security of transmission, reduce thermal production, better prevention signal interference. The parts which are not described in the present application belong to the prior art, and are not described in detail herein.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and it will be apparent to those skilled in the art that various modifications and variations can be made in the present invention; any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
1. A medical imaging robot, comprising: the system comprises a cloud service platform, a basic service end and an expert service end; the cloud service platform is provided with an information management system; the cloud service platform, the basic level server and the expert server are connected through a network transmission channel, and the cloud service platform comprises a data storage module, a data analysis module and a report generation module; the information management system adopts a layered architecture and comprises an application interaction layer and a block chain layer.
2. The medical imaging robot of claim 1, wherein the primary server comprises a report query module, a data collection module, and a case discussion module; the expert server comprises a case viewing module, a report auditing module and a case discussion module.
3. The medical imaging robot according to any one of claims 1-2, wherein the robot is configured in a layered processing manner, and comprises a data layer, a network layer, an interface layer, a storage layer, a processing layer, and an application layer.
4. The medical imaging robot of claim 1 or 3, wherein the data layer is for collecting medical imaging data information, the network layer is for transmitting information, the interface layer adopts multi-source heterogeneous data processing, the storage layer stores data information, the processing layer performs data processing and report generation, and the application layer comprises an information management system, a basic service end and an expert service end.
5. The medical imaging robot as claimed in any one of claims 1-4, wherein the interaction layer uses a Web terminal interface for interaction; one part of the blockchain layer is a P2P network that maintains the functions of the system to run and process queries and stores, and the other part is used for blockchain storage of record chains that have been validated.
6. The medical imaging robot as claimed in any one of claims 1 to 4, wherein the network transmission channel is an ipv6 high-speed transmission channel.
7. A control method for the medical imaging robot according to any one of claims 1 to 6, comprising the steps of:
s1: the basic-level server is responsible for acquiring medical image data, the acquired image data is uploaded to a cloud service platform through an IPv6 high-speed channel and is stored in time, data analysis is carried out through the cloud service platform, and a diagnosis report is obtained preliminarily;
s2: after step S1, the generated diagnosis report is pushed to the expert server, the diagnosis report is referred to by viewing the medical image and the expert diagnosis, the final diagnosis is made, and the diagnosis report is transmitted to the cloud service platform;
s3: and downloading an expert diagnosis report by the basic service terminal to confirm diagnosis.
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| CN112000742A (en) * | 2020-08-26 | 2020-11-27 | 德鲁动力科技(海南)有限公司 | Interaction method of foot type robot and block chain |
| CN112109096A (en) * | 2020-09-21 | 2020-12-22 | 深圳市明锐信息科技有限公司 | High-precision medical image robot and identification method thereof |
| CN113961634A (en) * | 2021-11-18 | 2022-01-21 | 贵州电网有限责任公司 | Staff health data acquisition method |
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Application publication date: 20200421 |