CN110200648A - A kind of medical knee joint rehabilitation nursing system and information processing method - Google Patents
A kind of medical knee joint rehabilitation nursing system and information processing method Download PDFInfo
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- CN110200648A CN110200648A CN201910296859.4A CN201910296859A CN110200648A CN 110200648 A CN110200648 A CN 110200648A CN 201910296859 A CN201910296859 A CN 201910296859A CN 110200648 A CN110200648 A CN 110200648A
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
- A61B6/50—Clinical applications
- A61B6/505—Clinical applications involving diagnosis of bone
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
- A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
- A61B6/5211—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data
Abstract
The invention belongs to knee joint recovery nursing technique field, a kind of medical knee joint rehabilitation nursing system and information processing method are disclosed, medical X-ray scenograph is utilized to acquire knee joint image data；Using sensor acquisition motion of knee joint number, uphold curvature, muscular strength data information；Enhancing processing is carried out using knee joint image of the image processing software to acquisition by image enhancement module；Knee joint recovery run duration is set using timer by movement timing module；Massage operation is carried out to the knee joint after rehabilitation exercise using massager by massage module；Knee joint recovery is assessed according to the collected data using appraisal procedure by evaluation module；Knee joint image, motion of knee joint related data and the rehabilitation assessment result of display display acquisition are utilized by display module.Assessment result of the present invention is more objective, simple to operate, is easy to repeat to realize and result is stablized, improve knee joint recovery effect.
Description
Technical field
The invention belongs to knee joint recovery nursing technique field more particularly to a kind of medical knee joint rehabilitation nursing system and
Information processing method.
Background technique
Knee joint is made of distal part of femur, proximal ends of tibia and kneecap, is the most complicated joint of human body maximum；Knee osteoarthritis
It is the most common skeletal muscle disease and the main reason for the middle-aged and the old is disabled, 85% total knee replacement is due to kneecap
Arthritis.The common problem of total knee replacement first is that the processing of bone defect, bone defect position can betide shin bone, femur and
Kneecap is more common in tibial plateau bone defect, and distal femur bone defect is low compared with the incidence of tibial bone defect, but distal femur bone lacks
Damage, which can increase, kneed bends and stretches gap, especially buckling gap.First total knee replacement bone defect reason mainly includes shin
Abrasion, osteonecrosis, condylar agenesis, wound, inflammatory reaction of bone platform etc.；The reason of total knee replacement bone overhaul technology defect
It mainly include arthritis, angulation deformity, ischemic necrosis, stress shielding, High Tibial Osteotomy history or total knee replacement
History of operation and prosthese take out misoperation, or see infection joint replacement, the first-phase debridement stage.In total knee arthroplasty
Also bone defect can occur, be especially more common in total knee replacement overhaul technology, reason includes that osteotomy is excessive, infects, in overhaul technology
Take out that prosthese is improper causes.Patient needs reasonably to handle bone defect, accurately places prosthese and establishes firm bone-prosthese and connect
Interface is touched, for prosthese provides enough supports and obtains satisfied surgical effect.However, existing knee joint recovery nursing system is adopted
When collecting knee joint image, poor in image definition influences to observe；Meanwhile cannot provide and motion of knee joint is assessed, influence knee joint
Rehabilitation efficacy.
In conclusion problem of the existing technology is:
When existing knee joint recovery nursing system acquisition knee joint image, poor in image definition influences to observe；Meanwhile no
It can provide and motion of knee joint is assessed, influence knee joint recovery effect.
And in the prior art, x-ray image is not analyzed using depth learning technology, it can not be to various pictures
There are good adaptability, poor robustness；Poor in image definition.
Summary of the invention
In view of the problems of the existing technology, the present invention provides at a kind of medical knee joint rehabilitation nursing system and information
Reason method.
The invention is realized in this way a kind of information processing method of medical knee joint rehabilitation nursing system includes:
Step 1 acquires knee joint image data using medical X-ray scenograph by knee joint image capture module；It collects
Several knee joint high-resolution natural images；High-resolution natural image is transformed into from red, green, blue RGB color
Brightness, chroma blue, red color YCbCr color space；All luminance pictures of knee joint image are collected to instruct as high-resolution
Practice image setWhereinIndicate pth width high-resolution luminance image, n indicates the quantity of image；
Motion of knee joint number is acquired using sensor by exercise data acquisition module, upholds curvature, muscular strength data letter
Breath；
Step 2, central control module is by image enhancement module using image processing software to the knee joint image of acquisition
Carry out enhancing processing；Training deep neural network is constructed, and training obtains corresponding network model；X-ray image data are inputted
Into trained deep neural network, the parameter matrix of corresponding gain image is obtained；By the parameter of obtained gain image
Matrix and former x-ray image carry out data processing；Output data treated x-ray image；
Knee joint recovery run duration is set using timer by movement timing module；Massage is utilized by massage module
Device carries out massage operation to the knee joint after rehabilitation exercise；
Step 3 according to the collected data assesses knee joint recovery using appraisal procedure by evaluation module；Structure
Build an assessment models, the assessment models include at least to judge movement angle difference first angle difference threshold value, second jiao
Poor threshold value and the poor threshold epsilon that moves forward and backward to judge to move forward and backward value are spent, and the assessment depending on each threshold value is classified knot
Fruit；
Kneed single group three-dimensional six-degree-of-freedomovement movement data and the kneed single group three-dimensional six in right side on the left of synchronous acquisition
Freedom degree exercise data, every group of three-dimensional six-degree-of-freedomovement movement data include at least bend and stretch angle, inside and outside flip angle, inside and outside rotation angle and
Move forward and backward value；
The kneed three-dimensional six-degree-of-freedomovement movement data of left and right side is compared, and calculate in two groups of data about
Bend and stretch angle, inside and outside flip angle, inside and outside rotation angle and the difference for moving forward and backward value；
The difference is input in the assessment models, to obtain corresponding assessment classification results；If three differential seat angles
Respectively less than first angle difference threshold value and move forward and backward value difference be less than move forward and backward poor threshold value, then assessment models output first assessment etc.
Grade；If at least one differential seat angle is in the closed interval that first angle difference threshold value and second angle difference threshold value are constituted and moves forward and backward value
Difference, which is less than, moves forward and backward poor threshold value, then assessment models export the second evaluation grade；If at least one differential seat angle is more than or equal to second
Differential seat angle threshold value and move forward and backward value difference be less than move forward and backward poor threshold value or three differential seat angles be respectively less than second angle difference threshold value and
Value difference is moved forward and backward more than or equal to poor threshold value is moved forward and backward, then assessment models export third evaluation grade；If at least two angles
Difference is more than or equal to second angle difference threshold value or at least one differential seat angle is more than or equal to second angle difference threshold value and moves forward and backward value difference
More than or equal to poor threshold value is moved forward and backward, then assessment models export the 4th evaluation grade；
Step 4, knee joint image, motion of knee joint related data by display module using display display acquisition
And rehabilitation assessment result.
Further, the building training deep neural network, and training obtains corresponding network model, step specific as follows
It is rapid:
Acquire original training image and the preferable image of corresponding reinforcing effect；
Depth network model is constructed, determines the number of plies, training method, frequency of training of model；
X-ray image is sent into network and is trained, obtains optimal training parameter using the training method for having supervision.
Further, the parameter matrix of the gain image that will be obtained and former x-ray image carry out data processing, specific data
The process of processing is as follows:
The pixel average for calculating regional area of each pixel centered on its own in former x-ray image, by following
This formula is calculated:
Wherein, (i, j) is pixel center, and x (i, j) is the gray value that certain in image is put, and window size is (2n+1) * (2n
+ 1), wherein n is an integer；This certain window area can not be square；mx(i, j) is exactly being averaged for this pixel
Value；The gray value f (i, j) for the enhanced image pixel finally wanted is calculated by this formula:
F (i, j)=mx(i, j)+G (i, j) [x (i, j)-mx(i, j)]
Wherein, G (i, j) is exactly the parameter matrix of gain image.
Further, by high-resolution training image collectionIn all images be divided into from top to bottom, left to right
Overlapped rectangular image block；
All rectangular image blocks are indicated with column vector respectively；
It collects all column vectors and generates high-resolution training image blocks collectionWhereinIt indicatesIn
P-th of column vector, NsThe quantity for indicating training image blocks, withIt corresponds.
Further, all obtained high-definition picture blocks are stitched together, overlapping region pixel is averaged, and is obtained most
Whole high resolution output luminance picture
Another object of the present invention is to provide a kind of message handling program of medical knee joint rehabilitation nursing system, applications
The medical knee joint rehabilitation nursing system is realized in the message handling program of terminal, the medical knee joint rehabilitation nursing system
The information processing method of system.
Another object of the present invention is to provide a kind of terminal, the terminal, which is carried, realizes the medical knee joint rehabilitation shield
The processor of the information processing method of reason system.
Another object of the present invention is to provide a kind of computer readable storage mediums, including instruction, when it is in computer
When upper operation, so that computer executes the information processing method of the medical knee joint rehabilitation nursing system.
Another object of the present invention is to provide a kind of information processings for implementing the medical knee joint rehabilitation nursing system
The medical knee joint rehabilitation nursing system of method, the medical knee joint rehabilitation nursing system include:
Knee joint image capture module, connect with central control module, for acquiring knee joint by medical X-ray scenograph
Image data；
Exercise data acquisition module, connect with central control module, for by sensor acquisition motion of knee joint number,
Uphold curvature, muscular strength data information；
Central control module, with knee joint image capture module, exercise data acquisition module, image enhancement module, movement
Timing module, massage module, evaluation module, display module connection, work normally for controlling modules by single-chip microcontroller；
Image enhancement module is connect with central control module, for the knee joint figure by image processing software to acquisition
As carrying out enhancing processing；
Timing module is moved, is connect with central control module, for setting knee joint recovery run duration by timer；
Massage module is connect with central control module, for by massager to the knee joint after rehabilitation exercise carry out by
Rub operation；
Evaluation module is connect with central control module, for passing through appraisal procedure according to the collected data to knee joint health
It is assessed again；
Display module is connect with central control module, for knee joint image, the knee joint by display display acquisition
Motion-dependent data and rehabilitation assessment result.
Another object of the present invention is to provide a kind of medical knee passes for carrying the medical knee joint rehabilitation nursing system
Save rehabilitation nursing equipment.
Advantages of the present invention and good effect are as follows:
The present invention analyzes x-ray image using depth learning technology by image enhancement module, by unartificial dry
Most suitable parameter required for pre- means are found can have good adaptability to various pictures in this way,
There is stronger robustness；Greatly improve image definition；Meanwhile assessment models are constructed by evaluation module, and acquire left and right
The kneed three-dimensional six-degree-of-freedomovement movement data in side, for the dynamic changes of knee joint during the motion, to two sides
After data make difference, assessment solution is carried out to difference with assessment models, in assessment models, two sides kneed three-dimensional six are freely
Bending and stretching angle, inside and outside flip angle, inside and outside rotation angle and move forward and backward the correspondence difference of value as assessment models in degree exercise data
Input parameter assessed, the threshold value that sets in Evaluation model obtains assessment classification results, and assessment result is more objective,
It is simple to operate, it is easy to repeat to realize and result is stablized, improves knee joint recovery effect.
The present invention acquires knee joint image data using medical X-ray scenograph by knee joint image capture module；It collects
Several knee joint high-resolution natural images；By high-resolution natural image from red, green, blue RGB color space conversion to
Brightness, chroma blue, red color YCbCr color space；All luminance pictures of knee joint image are collected to instruct as high-resolution
Practice image setWhereinIndicate pth width high-resolution luminance image, n indicates the quantity of image, can get clear
Clear knee joint image.
Detailed description of the invention
Fig. 1 is medical knee joint rehabilitation nursing system construction drawing provided in an embodiment of the present invention.
In figure: 1, knee joint image capture module；2, exercise data acquisition module；3, central control module；4, image increases
Strong module；5, timing module is moved；6, massage module；7, evaluation module；8, display module.
Specific embodiment
In order to further understand the content, features and effects of the present invention, the following examples are hereby given, and cooperate attached drawing
Detailed description are as follows.
When existing knee joint recovery nursing system acquisition knee joint image, poor in image definition influences to observe；Meanwhile no
It can provide and motion of knee joint is assessed, influence knee joint recovery effect.And in the prior art, depth learning technology is not utilized
X-ray image is analyzed, can not have good adaptability, poor robustness to various pictures；Poor in image definition.
To solve the above problems, being explained in detail with reference to the accompanying drawing to structure of the invention.
As shown in Figure 1, medical knee joint rehabilitation nursing system provided in an embodiment of the present invention includes: knee joint Image Acquisition
Module 1, exercise data acquisition module 2, central control module 3, image enhancement module 4, movement timing module 5, massage module 6,
Evaluation module 7, display module 8.
Knee joint image capture module 1 is connect with central control module 3, is closed for acquiring knee by medical X-ray scenograph
Save image data；
Exercise data acquisition module 2 is connect with central control module 3, for acquiring motion of knee joint time by sensor
Number upholds curvature, muscular strength data information；
Central control module 3, with knee joint image capture module 1, exercise data acquisition module 2, image enhancement module 4,
It moves timing module 5, massage module 6, evaluation module 7, display module 8 to connect, for controlling modules just by single-chip microcontroller
Often work；
Image enhancement module 4 is connect with central control module 3, for the knee joint by image processing software to acquisition
Image carries out enhancing processing；
Timing module 5 is moved, is connect with central control module 3, when for setting knee joint recovery movement by timer
Between；
Massage module 6 is connect with central control module 3, for being carried out by massager to the knee joint after rehabilitation exercise
Massage operation；
Evaluation module 7 is connect with central control module 3, for passing through appraisal procedure according to the collected data to knee joint
Rehabilitation is assessed；
Display module 8 is connect with central control module 3, is closed for knee joint image, the knee by display display acquisition
Save motion-dependent data and rehabilitation assessment result.
As shown in Fig. 2, the information processing method of medical knee joint rehabilitation nursing system provided in an embodiment of the present invention includes:
S101 acquires knee joint image data using medical X-ray scenograph by knee joint image capture module 1；Pass through
Exercise data acquisition module 2 utilizes sensor acquisition motion of knee joint number, extension curvature, muscular strength data information.
S102, central control module 3 is by image enhancement module 4 using image processing software to the knee joint image of acquisition
Carry out enhancing processing；Knee joint recovery run duration is set using timer by movement timing module 5；Pass through massage module 6
Massage operation is carried out to the knee joint after rehabilitation exercise using massager.
S103 according to the collected data assesses knee joint recovery using appraisal procedure by evaluation module 7.
S104, by display module 8 using display display acquisition knee joint image, motion of knee joint related data and
Rehabilitation assessment result.
In step S101, knee joint image data is acquired using medical X-ray scenograph by knee joint image capture module；
Collect several knee joint high-resolution natural images；High-resolution natural image is turned from red, green, blue RGB color
Change to brightness, chroma blue, red color YCbCr color space；All luminance pictures of knee joint image are collected as high-resolution
Rate training image collectionWhereinIndicate pth width high-resolution luminance image, n indicates the quantity of image；
By high-resolution training image collectionIn all images be divided into phase mutual respect from top to bottom, left to right
Folded rectangular image block.
All rectangular image blocks are indicated with column vector respectively；
It collects all column vectors and generates high-resolution training image blocks collectionWhereinIt indicatesIn
P-th of column vector, Ns indicate the quantity of training image blocks, withIt corresponds.
All obtained high-definition picture blocks are stitched together, overlapping region pixel is averaged, and obtains final height
Resolution ratio exports luminance picture
The invention will be further described combined with specific embodiments below.
Embodiment 1
4 Enhancement Method of image enhancement module provided by the invention is as follows:
(1) training deep neural network is constructed, and training obtains corresponding network model；
(2) x-ray image data are input in trained deep neural network, obtain the parameter of corresponding gain image
Matrix；
(3) parameter matrix of obtained gain image and former x-ray image are subjected to data processing；
(4) output data treated x-ray image；
Step (1) provided by the invention constructs training deep neural network, and training obtains corresponding network model, specifically
Following steps:
Acquire original training image and the preferable image of corresponding reinforcing effect；
Depth network model is constructed, determines the number of plies, training method, frequency of training of model；
X-ray image is sent into network and is trained, obtains optimal training parameter using the training method for having supervision；
The parameter matrix of obtained gain image and former x-ray image are counted described in step (3) provided by the invention
According to processing, the process of specific data processing is as follows:
The pixel average for calculating regional area of each pixel centered on its own in former x-ray image, by following
This formula is calculated:
Wherein, (i, j) is pixel center, and x (i, j) is the gray value that certain in image is put, and window size is (2n+1) * (2n
+ 1), wherein n is an integer；This certain window area can not be square；mx(i, j) is exactly being averaged for this pixel
Value；The gray value f (i, j) for the enhanced image pixel finally wanted is calculated by this formula:
F (i, j)=mx(i, j)+G (i, j) [x (i, j)-mx(i, j)] (2)
Wherein, G (i, j) is exactly the parameter matrix of gain image.
Embodiment 2
7 appraisal procedure of evaluation module provided by the invention is as follows:
1) assessment models are constructed, the assessment models are included at least to judge that the first angle of movement angle difference is poor
Threshold value, second angle difference threshold value and the poor threshold epsilon that moves forward and backward to judge to move forward and backward value, and depending on each threshold value
Assess classification results；
2) the kneed single group of kneed single group three-dimensional six-degree-of-freedomovement movement data and right side is three-dimensional on the left of synchronous acquisition
Six-degree-of-freedomovement movement data, every group of three-dimensional six-degree-of-freedomovement movement data, which includes at least, bends and stretches angle, inside and outside flip angle, inside and outside rotation angle
With move forward and backward value；
3) the kneed three-dimensional six-degree-of-freedomovement movement data of left and right side is compared, and calculates and is closed in two groups of data
In bending and stretching angle, inside and outside flip angle, inside and outside rotation angle and the difference for moving forward and backward value；
4) difference is input in the assessment models, to obtain corresponding assessment classification results；If three angles
Difference is respectively less than first angle difference threshold value and moves forward and backward value difference less than poor threshold value is moved forward and backward, then assessment models output first is assessed
Grade；If at least one differential seat angle is in the closed interval that first angle difference threshold value and second angle difference threshold value are constituted and moves forward and backward
Value difference, which is less than, moves forward and backward poor threshold value, then assessment models export the second evaluation grade；If at least one differential seat angle is more than or equal to the
It two differential seat angle threshold values and moves forward and backward value difference and is less than and move forward and backward poor threshold value or three differential seat angles are respectively less than second angle difference threshold value
And moving forward and backward value difference more than or equal to poor threshold value is moved forward and backward, then assessment models export third evaluation grade；If at least two jiaos
Degree difference is more than or equal to second angle difference threshold value or at least one differential seat angle is more than or equal to second angle difference threshold value and moves forward and backward value
Difference, which is more than or equal to, moves forward and backward poor threshold value, then assessment models export the 4th evaluation grade.
In the above-described embodiments, can come wholly or partly by software, hardware, firmware or any combination thereof real
It is existing.When using entirely or partly realizing in the form of a computer program product, the computer program product include one or
Multiple computer instructions.When loading on computers or executing the computer program instructions, entirely or partly generate according to
Process described in the embodiment of the present invention or function.The computer can be general purpose computer, special purpose computer, computer network
Network or other programmable devices.The computer instruction may be stored in a computer readable storage medium, or from one
Computer readable storage medium is transmitted to another computer readable storage medium, for example, the computer instruction can be from one
A web-site, computer, server or data center pass through wired (such as coaxial cable, optical fiber, Digital Subscriber Line (DSL)
Or wireless (such as infrared, wireless, microwave etc.) mode is carried out to another web-site, computer, server or data center
Transmission).The computer-readable storage medium can be any usable medium or include one that computer can access
The data storage devices such as a or multiple usable mediums integrated server, data center.The usable medium can be magnetic Jie
Matter, (for example, floppy disk, hard disk, tape), optical medium (for example, DVD) or semiconductor medium (such as solid state hard disk Solid
State Disk (SSD)) etc..
The above is only the preferred embodiments of the present invention, and is not intended to limit the present invention in any form,
Any simple modification made to the above embodiment according to the technical essence of the invention, equivalent variations and modification, belong to
In the range of technical solution of the present invention.
Claims (10)
1. a kind of information processing method of medical knee joint rehabilitation nursing system, which is characterized in that the medical knee joint rehabilitation
The information processing method of nursing system includes:
Step 1 acquires knee joint image data using medical X-ray scenograph by knee joint image capture module；Collect several
Knee joint high-resolution natural image；By high-resolution natural image from red, green, blue RGB color be transformed into brightness,
Chroma blue, red color YCbCr color space；All luminance pictures of knee joint image are collected as high-resolution training image
CollectionWhereinIndicate pth width high-resolution luminance image, n indicates the quantity of image；
Motion of knee joint number is acquired using sensor by exercise data acquisition module, upholds curvature, muscular strength data information；
Step 2, central control module are carried out by image enhancement module using knee joint image of the image processing software to acquisition
Enhancing processing；Training deep neural network is constructed, and training obtains corresponding network model；X-ray image data are input to instruction
In the deep neural network perfected, the parameter matrix of corresponding gain image is obtained；By the parameter matrix of obtained gain image
Data processing is carried out with former x-ray image；Output data treated x-ray image；
Knee joint recovery run duration is set using timer by movement timing module；Massager pair is utilized by massage module
Knee joint after rehabilitation exercise carries out massage operation；
Step 3 according to the collected data assesses knee joint recovery using appraisal procedure by evaluation module；Building one
Assessment models, the assessment models are included at least to judge that first angle difference threshold value, the second angle of movement angle difference are poor
Threshold value and the poor threshold epsilon that moves forward and backward to judge to move forward and backward value, and the assessment classification results depending on each threshold value；
The kneed single group three-dimensional six of kneed single group three-dimensional six-degree-of-freedomovement movement data and right side is free on the left of synchronous acquisition
Exercise data is spent, every group of three-dimensional six-degree-of-freedomovement movement data, which includes at least, bends and stretches angle, inside and outside flip angle, inside and outside rotation angle and front and back
Shift value；
The kneed three-dimensional six-degree-of-freedomovement movement data of left and right side is compared, and is calculated in two groups of data about bending and stretching
Angle, inside and outside flip angle, inside and outside rotation angle and the difference for moving forward and backward value；
The difference is input in the assessment models, to obtain corresponding assessment classification results；If three differential seat angles are small
In first angle difference threshold value and value difference is moved forward and backward less than poor threshold value is moved forward and backward, then assessment models export the first evaluation grade；
If at least one differential seat angle is in the closed interval that first angle difference threshold value and second angle difference threshold value are constituted and moves forward and backward value difference
Less than poor threshold value is moved forward and backward, then assessment models export the second evaluation grade；If at least one differential seat angle is more than or equal to second jiao
It spends poor threshold value and moves forward and backward value difference and be less than and move forward and backward poor threshold value or three differential seat angles are respectively less than second angle difference threshold value and preceding
Displacement value difference, which is more than or equal to, afterwards moves forward and backward poor threshold value, then assessment models export third evaluation grade；If at least two differential seat angles
It is more than or equal to the poor threshold value of second angle more than or equal to the poor threshold value of second angle or at least one differential seat angle and to move forward and backward value difference big
Poor threshold value is moved forward and backward in being equal to, then assessment models export the 4th evaluation grade；
Step 4 utilizes knee joint image, motion of knee joint related data and the health of display display acquisition by display module
Multiple assessment result.
2. the information processing method of medical knee joint rehabilitation nursing system as described in claim 1, which is characterized in that the structure
Trained deep neural network is built, and training obtains corresponding network model, step specific as follows:
Acquire original training image and the preferable image of corresponding reinforcing effect；
Depth network model is constructed, determines the number of plies, training method, frequency of training of model；
X-ray image is sent into network and is trained, obtains optimal training parameter using the training method for having supervision.
3. the information processing method of medical knee joint rehabilitation nursing system as described in claim 1, which is characterized in that described to incite somebody to action
The parameter matrix of the gain image arrived and former x-ray image carry out data processing, and the process of specific data processing is as follows:
The pixel average for calculating regional area of each pixel centered on its own in former x-ray image, by it is following this
Formula is calculated:
Wherein, (i, j) is pixel center, and x (i, j) is the gray value that certain in image is put, and window size is (2n+1) * (2n+1),
Wherein n is an integer；This certain window area can not be square；mx(i, j) is exactly the average value of this pixel；Most
The gray value f (i, j) for the enhanced image pixel wanted eventually is calculated by this formula:
F (i, j)=mx(i, j)+G (i, j) [x (i, j)-mx(i, j)]
Wherein, G (i, j) is exactly the parameter matrix of gain image.
4. the information processing method of medical knee joint rehabilitation nursing system as described in claim 1,
By high-resolution training image collectionIn all images be divided into from top to bottom, left to right it is overlapped
Rectangular image block；
All rectangular image blocks are indicated with column vector respectively；
It collects all column vectors and generates high-resolution training image blocks collectionWhereinIt indicatesIn p-th
Column vector, NsThe quantity for indicating training image blocks, withIt corresponds.
5. the information processing method of medical knee joint rehabilitation nursing system as described in claim 1,
All obtained high-definition picture blocks are stitched together, overlapping region pixel is averaged, and obtains final high-resolution
Rate exports luminance picture
6. a kind of message handling program of medical knee joint rehabilitation nursing system is applied to terminal, which is characterized in that described medical
The message handling program of knee joint recovery nursing system realizes medical knee joint rehabilitation described in Claims 1 to 5 any one
The information processing method of nursing system.
7. a kind of terminal, which is characterized in that the terminal, which is carried, realizes medical knee joint described in Claims 1 to 5 any one
The processor of the information processing method of rehabilitation nursing system.
8. a kind of computer readable storage medium, including instruction, when run on a computer, so that computer is executed as weighed
Benefit requires the information processing method of medical knee joint rehabilitation nursing system described in 1-5 any one.
9. a kind of medical knee joint health for the information processing method for implementing medical knee joint rehabilitation nursing system described in claim 1
Multiple nursing system, which is characterized in that the medical knee joint rehabilitation nursing system includes:
Knee joint image capture module, connect with central control module, for acquiring knee joint image by medical X-ray scenograph
Data；
Exercise data acquisition module, connect with central control module, for acquiring motion of knee joint number by sensor, upholding
Curvature, muscular strength data information；
Central control module, with knee joint image capture module, exercise data acquisition module, image enhancement module, movement timing
Module, massage module, evaluation module, display module connection, work normally for controlling modules by single-chip microcontroller；
Image enhancement module is connect with central control module, for by image processing software to the knee joint image of acquisition into
Row enhancing processing；
Timing module is moved, is connect with central control module, for setting knee joint recovery run duration by timer；
Massage module is connect with central control module, for carrying out massage behaviour to the knee joint after rehabilitation exercise by massager
Make；
Evaluation module is connect with central control module, for by appraisal procedure according to the collected data to knee joint recovery into
Row assessment；
Display module is connect with central control module, for the knee joint image by display display acquisition, motion of knee joint
Related data and rehabilitation assessment result.
10. a kind of medical knee joint rehabilitation nursing equipment for carrying medical knee joint rehabilitation nursing system described in claim 9.
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