CN110097970A - A kind of facial paralysis diagnostic system and its system method for building up based on deep learning - Google Patents
A kind of facial paralysis diagnostic system and its system method for building up based on deep learning Download PDFInfo
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- CN110097970A CN110097970A CN201910391221.9A CN201910391221A CN110097970A CN 110097970 A CN110097970 A CN 110097970A CN 201910391221 A CN201910391221 A CN 201910391221A CN 110097970 A CN110097970 A CN 110097970A
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- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT 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
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Abstract
The invention discloses a kind of facial paralysis diagnostic system and its system method for building up based on deep learning replies module the system comprises image pick-up device, picture recognition module, image recognition library, facial paralysis medical knowledge base, question and answer knowledge base, reasoning diagnosis and replies feedback module；Image pick-up device is used to the facial image information of user being converted to electric signal, input picture identification module；Picture recognition module utilizes the facial image identification information in image recognition library, for analyzing the human face image information of user's input, analyzes the face feature of user；Reasoning diagnosis replies the face feature that module receives picture recognition module, retrieves facial paralysis medical knowledge base and question and answer knowledge base according to face feature, obtains the highest answer of confidence level, be sent to answer feedback module；Replying feedback module will reply through language, text or photo feedback to user.It solves the problems, such as existing by search engine to obtain medical knowledge time-consuming, information accuracy difficulty is sentenced and can not " facial diagnosis ".
Description
Technical field
The present invention relates to a kind of medical diagnosis systems, and in particular to a kind of facial paralysis diagnostic system based on deep learning and its
System method for building up.
Background technique
In the past, in such a way that search engine obtains knowledge, user's a large amount of time is on the one hand wasted；On the other hand it is curing
The field of disease inquiry is treated, the good and bad jumbled together for information source, and user's resolving ability is limited, and there are misguided possibilities.Traditional asks
Answering community needs human-edited's answer, and period of reservation of number is longer, along with the development of the artificial intelligence technologys such as NLP, knowledge mapping,
It provides instant Health information service in the form of question and answer for user to be possibly realized, with the development of artificial intelligence, image recognition
The maturation of technology, medical diagnosis, which is also developed to from communication, may be implemented " facial diagnosis ".
So needing a novel intelligent diagnosis system, which can satisfy user to specific facial paralysis medical field
Diagnostic requirements can recognize that the changes in faces of user and quickly can correctly provide diagnosis.
Summary of the invention
The purpose of the present invention is to provide a kind of facial paralysis diagnostic system and its system method for building up based on deep learning, use
Medical knowledge is obtained to solve the problems, such as existing by search engine, and time-consuming, information accuracy difficulty is sentenced and can not " facial diagnosis ".
In order to solve the above technical problems, the present invention adopts the following technical scheme:
A kind of facial paralysis diagnostic system based on deep learning, the system comprises image pick-up device, picture recognition module, images
Identify that library, facial paralysis medical knowledge base, question and answer knowledge base, reasoning diagnosis reply module and reply feedback module；
Described image pick device is used to the facial image information of user being converted to electric signal, input picture identification module；
Described image identification module utilizes the facial image identification information in image recognition library, for analyzing the face figure of user's input
As information, the face feature of user is analyzed；
The reasoning diagnosis replies the face feature that module receives picture recognition module, retrieves facial paralysis medicine according to face feature and knows
Know library and question and answer knowledge base, when lacking dependent diagnostic input, the diagnosis input content of missing be sent to answer feedback module,
User's supplemental information is fed back to, after obtaining complete diagnosis input, reasoning diagnosis replies module and obtains that confidence level is highest to be answered
Case is sent to answer feedback module；
The answer feedback module will be for that will reply through language, text or photo feedback to user.
Preferably, above-mentioned image pick-up device includes the camera shooting of the camera of smart machine, the camera of mobile phone and computer
Head, for capturing face's live image of one section of user.
Preferably, it includes countenance variation, symptom and movement that above-mentioned picture recognition module, which analyzes the problem content come,.
Preferably, above-mentioned answer feedback module by the microphone of smart machine or display, mobile phone loudspeaker or
Screen, the loudspeaker of computer or screen are by language, text or photo feedback to user.
A kind of facial paralysis diagnostic system method for building up based on deep learning, method for building up specifically comprise the following steps:
Step1: image pick-up device needed for establishing system operation and the hardware for replying feedback module, realize system and user it
Between information interaction；
Step2: the image recognition library based on existing maturation constructs picture recognition module, writing system software；
Step3: the existing medical knowledge relevant to facial paralysis of typing constructs facial paralysis medical knowledge base, and in system operation not
It is disconnected to improve the facial paralysis medical knowledge base constructed；
Step4: being based on existing network question and answer relevant to facial paralysis, constructs question and answer knowledge base；
Step5: in system operation, tissue doctor is reviewed modification to system replies result, and system passes through doctor's
Modification is checked, constantly improve and updates facial paralysis knowledge base and question and answer knowledge base.
Preferably, existing medical knowledge relevant to the facial paralysis source in above-mentioned Step3 includes books, periodical and height
Grade meeting paper.
Preferably, the existing network question and answer relevant to facial paralysis in above-mentioned Step4 include the question and answer net of professional forum, hospital
The medical software information of page and profession.
The present invention has the advantage that
It takes the present invention is based on after the scheme of the facial paralysis diagnostic system of deep learning, realizes to existing medical knowledge and question and answer system
The combination of system realizes and carries out " facial diagnosis " to user；On the basis of integrating existing medical system and question answering system knowledge, in conjunction with doctor
Raw Real-time Feedback synchronous refresh knowledge base, completes and provides the system Construction correctly diagnosed to user's disease, so that user can
To obtain reliable medical advice or medical diagnosis in time by the system.
Detailed description of the invention
Fig. 1 is a kind of work flow diagram of the facial paralysis diagnostic system embodiment based on deep learning of the present invention；
Fig. 2 is a kind of process of construction flow chart of the facial paralysis diagnostic system method for building up embodiment based on deep learning of the present invention；
Fig. 3 is that a kind of face of the picture recognition module detection of facial paralysis diagnostic system embodiment based on deep learning of the present invention is special
The sign point location drawing.
Specific embodiment
Embodiments of the present invention are illustrated by particular specific embodiment below, those skilled in the art can be by this explanation
Content disclosed by book is understood other advantages and efficacy of the present invention easily.
It should be clear that this specification structure depicted in this specification institute accompanying drawings, ratio, size etc., only to cooperate specification to be taken off
The content shown is not intended to limit the invention enforceable qualifications so that those skilled in the art understands and reads, therefore
Do not have technical essential meaning, the modification of any structure, the change of proportionate relationship or the adjustment of size are not influencing the present invention
Under the effect of can be generated and the purpose that can reach, it should all still fall in disclosed technology contents and obtain the model that can cover
In enclosing.Meanwhile cited such as "upper", "lower", " left side ", the right side in this specification ", the term of " centre ", be merely convenient to chat
That states is illustrated, rather than to limit the scope of the invention, relativeness is altered or modified, and is changing skill without essence
It is held in art, when being also considered as the enforceable scope of the present invention.
Embodiment 1
Referring to Fig. 1, a kind of facial paralysis diagnostic system based on deep learning, the system comprises image pick-up devices, image recognition
Module, image recognition library, facial paralysis medical knowledge base, question and answer knowledge base, reasoning diagnosis reply module and reply feedback module；
Described image pick device is used to the facial image information of user being converted to electric signal, input picture identification module；
Described image identification module utilizes the facial image identification information in image recognition library, for analyzing the face figure of user's input
As information, the face feature of user is analyzed, referring to Fig. 3, picture recognition module is distributed for face muscle, to 68 spies in figure
Sign point is identified that the characteristics of motion of tracking characteristics point analyzes user's facial muscle motion conditions, to carry out medical diagnosis on disease；
The reasoning diagnosis replies the face feature that module receives picture recognition module, retrieves facial paralysis medicine according to face feature and knows
Know library and question and answer knowledge base, when lacking dependent diagnostic input, the diagnosis input content of missing be sent to answer feedback module,
User's supplemental information is fed back to, after obtaining complete diagnosis input, reasoning diagnosis replies module and obtains that confidence level is highest to be answered
Case is sent to answer feedback module；
The answer feedback module will be for that will reply through language, text or photo feedback to user.
In embodiment, above-mentioned image pick-up device includes taking the photograph for the camera of smart machine, the camera of mobile phone and computer
As head, for capturing face's live image of one section of user.
In embodiment, above-mentioned picture recognition module analyzes the problem content come and includes countenance variation, symptom and move
Make.
In embodiment, above-mentioned answer feedback module by the microphone of smart machine or display, mobile phone loudspeaker or
Person's screen, the loudspeaker of computer or screen are by language, text or photo feedback to user.
A kind of facial paralysis diagnostic system method for building up based on deep learning, method for building up specifically comprise the following steps:
Step1: image pick-up device needed for establishing system operation and the hardware for replying feedback module, realize system and user it
Between information interaction；
Step2: the image recognition library based on existing maturation constructs picture recognition module, writing system software；
Step3: the existing medical knowledge relevant to facial paralysis of typing constructs facial paralysis medical knowledge base, and in system operation not
It is disconnected to improve the facial paralysis medical knowledge base constructed；
Step4: being based on existing network question and answer relevant to facial paralysis, constructs question and answer knowledge base；
Step5: in system operation, tissue doctor is reviewed modification to system replies result, and system passes through doctor's
Modification is checked, constantly improve and updates facial paralysis knowledge base and question and answer knowledge base.
In embodiment, the relevant medical knowledge source of existing and facial paralysis in above-mentioned Step3 include books, periodical and
High-level meeting paper.
In embodiment, the existing network question and answer relevant to facial paralysis in above-mentioned Step4 include the question and answer of professional forum, hospital
The medical software information of webpage and profession.
Take that the present invention is based on after the scheme of the facial paralysis diagnostic system of deep learning, realize to existing medical knowledge and asking
The combination for answering system realizes and carries out " facial diagnosis " to user；On the basis of integrating existing medical system and question answering system knowledge, knot
The Real-time Feedback synchronous refresh knowledge base for closing doctor, completes and provides the system Construction correctly diagnosed to user's disease, so that with
Family can obtain reliable medical advice or medical diagnosis in time by the system.
In actual use, with the increase of number of users, the rising of number is diagnosed, result is checked with doctor,
By autonomous learning, diagnostic accuracy and reliability are gradually increasing system, with the gradually development of medical treatment obtain it is more accurate and
Reliable diagnosis capability.
Although above having used general explanation and specific embodiment, the present invention is described in detail, at this
On the basis of invention, it can be made some modifications or improvements, this will be apparent to those skilled in the art.Therefore,
These modifications or improvements without departing from theon the basis of the spirit of the present invention are fallen within the scope of the claimed invention.
Claims (7)
1. a kind of facial paralysis diagnostic system based on deep learning, it is characterised in that: the system comprises image pick-up devices, image
Identification module, image recognition library, facial paralysis medical knowledge base, question and answer knowledge base, reasoning diagnosis reply module and reply feedback module；
Described image pick device is used to the facial image information of user being converted to electric signal, input picture identification module；
Described image identification module utilizes the facial image identification information in image recognition library, for analyzing the face figure of user's input
As information, the face feature of user is analyzed；
The reasoning diagnosis replies the face feature that module receives picture recognition module, retrieves facial paralysis medicine according to face feature and knows
Know library and question and answer knowledge base, when lacking dependent diagnostic input, the diagnosis input content of missing be sent to answer feedback module,
User's supplemental information is fed back to, after obtaining complete diagnosis input, reasoning diagnosis replies module and obtains that confidence level is highest to be answered
Case is sent to answer feedback module；
The answer feedback module will be for that will reply through language, text or photo feedback to user.
2. a kind of facial paralysis diagnostic system based on deep learning according to claim 1, it is characterised in that: described image is picked up
Taking device includes the camera of the camera of smart machine, the camera of mobile phone and computer, for capturing the face of one section of user
Live image.
3. a kind of facial paralysis diagnostic system based on deep learning according to claim 1, it is characterised in that: described image is known
The problem of other module analysis comes out content includes countenance variation, symptom and movement.
4. a kind of facial paralysis diagnostic system based on deep learning according to claim 1, it is characterised in that: described to reply instead
It presents module and passes through the microphone of smart machine or the loudspeaker or screen of display, the loudspeaker of mobile phone or screen, computer
By language, text or photo feedback to user.
5. a kind of facial paralysis diagnostic system method for building up based on deep learning, which is characterized in that method for building up specifically includes as follows
Step:
Step1: image pick-up device needed for establishing system operation and the hardware for replying feedback module, realize system and user it
Between information interaction；
Step2: the image recognition library based on existing maturation constructs picture recognition module, writing system software；
Step3: the existing medical knowledge relevant to facial paralysis of typing constructs facial paralysis medical knowledge base, and in system operation not
It is disconnected to improve the facial paralysis medical knowledge base constructed；
Step4: being based on existing network question and answer relevant to facial paralysis, constructs question and answer knowledge base；
Step5: in system operation, tissue doctor is reviewed modification to system replies result, and system passes through doctor's
Modification is checked, constantly improve and updates facial paralysis knowledge base and question and answer knowledge base.
6. a kind of facial paralysis diagnostic system method for building up based on deep learning according to claim 5, it is characterised in that: described
The relevant medical knowledge source of existing and facial paralysis in Step3 includes books, periodical and high-level meeting paper.
7. a kind of facial paralysis diagnostic system method for building up based on deep learning according to claim 5, it is characterised in that: described
Existing network question and answer relevant to facial paralysis in Step4 include the medical software of professional forum, the question and answer webpage of hospital and profession
Information.
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| CN111126180A (en) * | 2019-12-06 | 2020-05-08 | 四川大学 | Facial paralysis severity automatic detection system based on computer vision |
| CN111553250A (en) * | 2020-04-25 | 2020-08-18 | 深圳德技创新实业有限公司 | Accurate facial paralysis degree evaluation method and device based on face characteristic points |
| CN111613306A (en) * | 2020-05-19 | 2020-09-01 | 南京审计大学 | Multi-feature fusion facial paralysis automatic evaluation method |
| CN111710439A (en) * | 2020-06-15 | 2020-09-25 | 广东徕康医疗科技有限公司 | Basic-level medical physical examination and auxiliary intelligent uploading system and method |
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