CN108960305A - A kind of scope scope interpretation system and method - Google Patents
A kind of scope scope interpretation system and method Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 19
- 201000010099 disease Diseases 0.000 claims abstract description 40
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims abstract description 40
- 238000002059 diagnostic imaging Methods 0.000 claims abstract description 33
- 238000013473 artificial intelligence Methods 0.000 claims abstract description 27
- 238000012545 processing Methods 0.000 claims abstract description 19
- 238000000605 extraction Methods 0.000 claims abstract description 12
- 208000024891 symptom Diseases 0.000 claims description 15
- 230000001225 therapeutic effect Effects 0.000 claims description 12
- 238000003384 imaging method Methods 0.000 claims description 7
- 230000005540 biological transmission Effects 0.000 claims description 5
- 239000011159 matrix material Substances 0.000 claims description 4
- 238000003709 image segmentation Methods 0.000 claims description 3
- 238000003708 edge detection Methods 0.000 claims description 2
- 238000003745 diagnosis Methods 0.000 abstract description 11
- 238000004458 analytical method Methods 0.000 abstract description 2
- 230000008901 benefit Effects 0.000 description 2
- 238000013135 deep learning Methods 0.000 description 2
- 230000003902 lesion Effects 0.000 description 2
- 208000027418 Wounds and injury Diseases 0.000 description 1
- 230000001427 coherent effect Effects 0.000 description 1
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- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 238000005194 fractionation Methods 0.000 description 1
- 210000001035 gastrointestinal tract Anatomy 0.000 description 1
- 208000014674 injury Diseases 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10068—Endoscopic image
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Abstract
The invention discloses a kind of scope scope interpretation system and method, system includes: input module, for receiving the medical imaging of follow-up patient；Image processing module, for carrying out pretreatment and feature extraction operation to the medical imaging；Artificial intelligence determination module obtains the probability that patient suffers from the disease for the standard feature collection of each disease in the follow-up feature of input and training picture library to be compared；Output module determines result for exporting artificial intelligence.It is assisted a physician using this system and carries out the analysis and diagnosis of image, picture correlation case history, advantageously reduce doctor's mistaken diagnosis, rate of missed diagnosis, it is particularly suitable for the hygienic institutes of base and remote districts that medical resource falls behind relatively, doctor's professional ability is relatively low, simultaneously the plenty of time can be saved for subsequent further make a definite diagnosis quickly by follow-up patient and one or more of disease associations.
Description
Technical field
The present invention relates to artificial intelligence field field, especially a kind of scope scope interpretation system and method.
Background technique
Certain diseases such as disease of digestive tract, it usually needs obtained by endoscope therapeutic apparatus coherent video and picture come for
Doctor provides the foundation for checking and diagnosing.After obtaining medical imaging and picture, doctor is made corresponding by actual observation
Medical treatment result, this has very high requirement to the experience and professional ability of doctor.If the clinical experience of doctor is less, business
There are part flaws for indifferent or corresponding image data, all may cause the fault of doctor's medical treatment result, make to patient
At great loss and injury.
Summary of the invention
Drawbacks described above based on the prior art, the embodiment of the present invention provide a kind of by artificial intelligence image recognition technology application
In the system and method for scope scope interpretation.
The present invention can realize in many ways, including method, system, unit or computer-readable medium, under
Discuss several embodiments of the present invention in face.
A kind of scope scope interpretation system, comprising:
Input module, for receiving the medical imaging of follow-up patient；
Image processing module, for carrying out pretreatment and feature extraction operation to the medical imaging；
In artificial intelligence determination module, follow-up feature for that will input and training picture library the standard feature collection of each disease into
Row compares, and obtains the probability that patient suffers from the disease；
Output module determines result for exporting artificial intelligence.
Further, the received follow-up patient medical image of input module includes real-time imaging and non real-time image, in real time
Image is the patient medical image acquired in real time by endoscope therapeutic apparatus, and non real-time image includes the medical imaging of storage and passes through
The medical imaging of network transmission.
Further, described image processing module specifically includes, for pre-processing to the medical imaging according to doctor
The practical frame number per second for treating image, is split as the picture of corresponding number.
Further, described image processing module is also used to carry out the picture image noise reduction, texture processing, edge inspection
Survey, image segmentation, the pretreatment operation of edge extracting.
Further, described image processing module is also used to carry out feature extraction, the image of extraction to image after pretreatment
Feature includes the follow-up feature that image texture characteristic, entropy feature and color matrix feature constitute patient's symptom image.
Further, the artificial intelligence determination module by the follow-up feature of patient's symptom image and trains each disease in picture library
The standard feature collection of disease is compared, and obtains similar between the follow-up feature and each disease criterion feature of patient's symptom image
Degree, and sorted according to the height of the similarity, show that patient suffers from the probability of each disease.
Further, the artificial intelligence determination module is correspondingly connected with grid module, sentences for realizing artificial intelligence
The long-range update of cover half type.
Further, the system is provided with interfacing expansion module, and the interface includes VGA, DVI and HDMI interface.
A kind of scope scope interpretation method, comprising steps of
Receive the medical imaging of follow-up patient；
The medical imaging is pre-processed, the follow-up feature of illness image is established；
The follow-up feature of patient's symptom image is compared with the standard feature collection of each disease in training picture library, is suffered from
Similarity between the follow-up feature of person's symptom image and each disease criterion feature, and show that patient suffers from respectively according to the similarity
The probability of disease.
The achievable positive advantageous effects of the embodiment of the present invention include: that lesion recognition capability is strong, and generalization ability is superior,
It is assisted a physician using this system and carries out the analysis and diagnosis of image, picture correlation case history, advantageously reduced doctor's mistaken diagnosis, fail to pinpoint a disease in diagnosis
Rate is particularly suitable for the hygienic institutes of base and remote districts that medical resource falls behind relatively, doctor's professional ability is relatively low；People
The standard feature collection of each disease in the follow-up feature of input and training picture library is compared work intelligent decision module, obtains patient
The probability suffered from the disease, can quickly by follow-up patient and one or more of disease associations, for it is subsequent further make a definite diagnosis save a large amount of when
Between.
Other aspects and advantages of the present invention become obviously according to detailed description with reference to the accompanying drawing, the attached drawing
The principle of the present invention is illustrated by way of example.
Detailed description of the invention
Examples of the present invention will be described by way of reference to the accompanying drawings, in which:
Fig. 1 is scope scope interpretation method flow diagram provided in an embodiment of the present invention.
Specific embodiment
All features disclosed in this specification or disclosed all methods or in the process the step of, in addition to mutually exclusive
Feature and/or step other than, can combine in any way.
Any feature disclosed in this specification unless specifically stated can be equivalent or with similar purpose by other
Alternative features are replaced.That is, unless specifically stated, each feature is an example in a series of equivalent or similar characteristics
?.
A kind of scope scope interpretation system, comprising:
Input module, for receiving the medical imaging of follow-up patient；
Image processing module, for carrying out pretreatment and feature extraction operation to the medical imaging；
In artificial intelligence determination module, follow-up feature for that will input and training picture library the standard feature collection of each disease into
Row compares, and obtains the probability that patient suffers from the disease；
Output module determines result for exporting artificial intelligence.
The received follow-up patient medical image of input module includes real-time imaging and non real-time image, and non real-time image includes
The medical imaging of storage and medical imaging by network transmission, real-time imaging is the patient acquired in real time by endoscope therapeutic apparatus
Medical imaging.The system can be formed by software, form web page or be formed in the form of hardware device, and system can be to the medical treatment of storage
Image carries out artificial intelligence judgement by the medical imaging of network transmission, can also directly connect with endoscope therapeutic apparatus, realization pair
The real-time state of an illness of the medical imaging of endoscope therapeutic apparatus acquisition determines, the image processor and this system of hospital's endoscope therapeutic apparatus at this time
Input module is connected, and realizes the intercommunication of medical imaging, and input module interface is provided with interfacing expansion module, interface include VGA,
DVI and HDMI interface can satisfy all kinds of image processors of different brands on the market.System receives non real-time image and carries out people
Work intelligent diagnostics are, it can be achieved that the hospital clinic for no economic capability purchase system or hardware device provides medical imaging artificial intelligence
The technical support that can be diagnosed；The real-time imaging that system receives endoscope therapeutic apparatus acquisition carries out artificial intelligence diagnosis, can by system or
Hardware device is directly mounted in the existing endoscope therapeutic apparatus of hospital, easy for installation, and at low cost, relevance grade is wide, is conducive to system
Popularization.
The Machine Vision Recognition chip that image processing module is selected dedicated for artificial intelligence image recognition, for medical treatment
Image carries out pretreatment and feature extraction operation.Pretreatment operation is carried out to medical imaging, is specifically included, according to medical imaging
Practical frame number per second, is split as the picture of corresponding number, and system is not less than 24 frame per second to the processing capacity of real-time imaging
Level.Image processing module carries out image noise reduction, texture processing, edge detection, image segmentation, edge to the picture of fractionation and mentions
It takes, then the pretreatment operations such as cutting carry out feature extraction to image after pretreatment, the characteristics of image of extraction includes image texture
Feature, entropy feature and color matrix feature constitute the follow-up feature of patient's symptom image.Feature is carried out to image after pretreatment to mention
When taking, scale invariant feature transfer algorithm and complete local binary patterns algorithm can be used to extract the figure in patient condition's image
As textural characteristics, while patient condition's image is split using gridding method and super-pixel method, extracts the entropy of image after segmentation
Feature and color matrix feature.
After artificial intelligence determination module receives the follow-up feature of patient's symptom image of image processing module transmission, by institute
Follow-up feature is stated to be compared with the standard feature collection of each disease in training picture library, obtain the follow-up feature of patient's symptom image with
Similarity between each disease criterion feature, and sorted according to the height of similarity, show that patient suffers from the probability of each disease.Each disease
Sick standard feature image is the standard illness image of the existing correspondence disease made a definite diagnosis, and the acquisition of standard feature collection is to utilize
Deep learning algorithm carries out feature extraction acquisition to each disease criterion illness image in training picture library, then utilizes deep learning
Follow-up special medical treatment is compared algorithm with the standard feature collection of each disease, obtains the follow-up feature and each disease of patient's symptom image
Similarity between standard feature.The lesion identification model and training method that the present invention utilizes, applicant are special in another invention
It is claimed in benefit, so it will not be repeated.
Optimally, artificial intelligence determination module is preset in SSD solid state hard disk, and integrated there are many artificial intelligence to determine mould
Type selects corresponding model for operator according to demand.Artificial intelligence determination module is correspondingly connected with grid module, is used for
Realize the long-range update of artificial intelligence decision model.
Output module exports artificial intelligence judgement result to system display module, or exports to endoscope therapeutic apparatus display
In, the raw video that system inputs endoscope therapeutic apparatus retains version without any processing, and simultaneously without any processing
Image version be directly output in therapeutic equipment display, and be left white in indicator screen display artificial intelligence determination module
Diagnostic result, the presentation result for carrying out medical imaging screenshotss in diagnosis and treatment process to doctor in this way do not have any influence.Output
Tri- kinds of major video interfaces of VGA, DVI, HDMI are equally arranged in module interface, can satisfy all kinds of displays of different brands on the market
Device.
A kind of scope scope interpretation method, comprising steps of
Receive the medical imaging of follow-up patient；
The medical imaging is pre-processed, the follow-up feature of illness image is established；
The follow-up feature of patient's symptom image is compared with the standard feature collection of each disease in training picture library, is suffered from
Similarity between the follow-up feature of person's symptom image and each disease criterion feature, and show that patient suffers from respectively according to the similarity
The probability of disease.
Different aspect, embodiment, embodiment or feature of the invention can be used alone or be used in any combination.
The invention is not limited to specific embodiments above-mentioned.The present invention, which expands to, any in the present specification to be disclosed
New feature or any new combination, and disclose any new method or process the step of or any new combination.
Claims (9)
1. a kind of scope scope interpretation system, characterized by comprising:
Input module, for receiving the medical imaging of follow-up patient；
Image processing module, for carrying out pretreatment and feature extraction operation to the medical imaging；
Artificial intelligence determination module, for comparing the standard feature collection of each disease in the follow-up feature of input and training picture library
It is right, obtain the probability that patient suffers from the disease；
Output module determines result for exporting artificial intelligence.
2. a kind of scope scope interpretation system according to claim 1, which is characterized in that the received follow-up of input module is suffered from
Person's medical imaging includes real-time imaging and non real-time image, and real-time imaging is the patient medical acquired in real time by endoscope therapeutic apparatus
Image, non real-time image include the medical imaging of storage and the medical imaging by network transmission.
3. a kind of scope scope interpretation system according to claim 1, which is characterized in that described image processing module is used for
The medical imaging is pre-processed, is specifically included, according to the practical frame number per second of medical imaging, is split as corresponding number
The picture of amount.
4. a kind of scope scope interpretation system according to claim 3, which is characterized in that described image processing module is also used
In to the picture progress image noise reduction, texture processing, edge detection, image segmentation, the pretreatment operation of edge extracting.
5. a kind of scope scope interpretation system according to claim 4, which is characterized in that described image processing module is also used
Image carries out feature extraction after to pretreatment, and the characteristics of image of extraction includes image texture characteristic, entropy feature and color matrix
The follow-up feature of feature composition patient's symptom image.
6. a kind of scope scope interpretation system according to claim 1, which is characterized in that the artificial intelligence determination module
The follow-up feature of patient's symptom image is compared with the standard feature collection of each disease in training picture library, obtains patient's symptom figure
Similarity between the follow-up feature of picture and each disease criterion feature, and according to described
The height of similarity sorts, and show that patient suffers from the probability of each disease.
7. a kind of scope scope interpretation system according to claim 1, which is characterized in that the artificial intelligence determination module
It is correspondingly connected with grid module, for realizing the long-range update of artificial intelligence decision model.
8. a kind of scope scope interpretation system according to claim 1, which is characterized in that the system is provided with interface expansion
Module is opened up, the interface includes VGA, DVI and HDMI interface.
9. a kind of scope scope interpretation method, which is characterized in that comprising steps of
Receive the medical imaging of follow-up patient；
The medical imaging is pre-processed, the follow-up feature of illness image is established；
The follow-up feature of patient's symptom image is compared with the standard feature collection of each disease in training picture library, obtains disease
The similarity between the follow-up feature and each disease criterion feature of image is levied, and show that patient suffers from each disease according to the similarity
Probability.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110021020A (en) * | 2019-04-18 | 2019-07-16 | 重庆金山医疗器械有限公司 | A kind of image detecting method, device and endoscopic system |
| CN111419414A (en) * | 2020-03-24 | 2020-07-17 | 德阳市人民医院 | Nursing box for cleaning wound and control method |
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| CN107133942A (en) * | 2017-04-24 | 2017-09-05 | 南京天数信息科技有限公司 | A kind of medical image processing method based on deep learning |
| CN107194158A (en) * | 2017-05-04 | 2017-09-22 | 深圳美佳基因科技有限公司 | A kind of disease aided diagnosis method based on image recognition |
| CN107492099A (en) * | 2017-08-28 | 2017-12-19 | 京东方科技集团股份有限公司 | Medical image analysis method, medical image analysis system and storage medium |
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| CN103324853A (en) * | 2013-06-25 | 2013-09-25 | 上海交通大学 | Similarity calculation system and method based on medical image features |
| CN107133942A (en) * | 2017-04-24 | 2017-09-05 | 南京天数信息科技有限公司 | A kind of medical image processing method based on deep learning |
| CN107194158A (en) * | 2017-05-04 | 2017-09-22 | 深圳美佳基因科技有限公司 | A kind of disease aided diagnosis method based on image recognition |
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Application publication date: 20181207 |