CN110111386A - The method for automatic measurement and system of structural angle in a kind of musculature - Google Patents
The method for automatic measurement and system of structural angle in a kind of musculature Download PDFInfo
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- CN110111386A CN110111386A CN201910389825.XA CN201910389825A CN110111386A CN 110111386 A CN110111386 A CN 110111386A CN 201910389825 A CN201910389825 A CN 201910389825A CN 110111386 A CN110111386 A CN 110111386A
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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- A61B5/45—For evaluating or diagnosing the musculoskeletal system or teeth
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- G06T2207/10—Image acquisition modality
- G06T2207/10132—Ultrasound image
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- G06T2207/20172—Image enhancement details
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Abstract
The invention discloses the method for automatic measurement and system of structural angle in a kind of musculature, method includes: to obtain muscle ultrasound image in real time in contraction of muscle movement, and pre-processed, and enhances image edge information；The normalization Radon transform algorithm of calling in muscle ultrasound image fascia and muscle bundle region divide, and obtain the first angle between deep fascia and preset trunnion axis；Radon transform is normalized to muscle bundle region, extracts multiple peak points in Radon transform matrix, and be weighted and averaged to the position and direction of all muscle fibres, obtains the second angle between muscle fibre and trunnion axis；First angle and the second angle are subjected to read group total, obtain the structural angle in musculature, structural angle is muscle pinniform angle.The present invention can naturally smooth, robust, automatically measure structural angle in musculature so that measurement result closer to true motion state, more can reflect the structure function of muscle.
Description
Technical field
The present invention relates to structures in the field of measuring technique of myoarchitecture angle more particularly to a kind of musculature
The method for automatic measurement and system of property angle.
Background technique
Muscle is the vital tissue for constituting human body, and major function is to generate the movement shunk and control body.Muscle knot
The mode that structure is transmitted to tendon and bone to muscular strength has an important influence.Myoarchitecture angle is bone such as muscle pinniform angle
The important indicator of flesh research.Myoarchitecture angle is related to the high strength of contraction of muscle, and doctor can be helped to understand muscle
Biomechanics characteristic, preferably assessment muscle function and pathological state, provide effective foundation for clinical diagnosis and rehabilitation assessment.
The measurement method of angle structural in musculature is largely taken at present is manually to delineate, this
Manual measurement mode is cumbersome, time-consuming, poor repeatability and very subjective, it is difficult to realize the analysis of muscle function in dynamic task.And
General method for automatic measurement equally exists certain deficiency, is mainly reflected in following three points: first point is structure that algorithm is surveyed
Property angle performance graph smoothness is low.The original signal of angle dynamic change detected by these methods is simultaneously unsmooth, exists
High dither rises and falls, and does not meet the rule of human muscle's system contractile motion, influences the precision of measurement.Second point is algorithm Shandong
Stick is low.These algorithms are often only applicable to the ultrasound image of certain a kind of muscle, degenerate on individual data collection serious, extensive energy
Power is poor.It is thirdly that algorithm automaticity is low.Entire operation process very complicated needs manual setting initial point or adjusts ginseng manually,
The degree of automation is not high.
Therefore, the prior art could be improved.
Summary of the invention
The technical problem to be solved in the present invention is that in view of the above drawbacks of the prior art, provide in a kind of musculature
The method for automatic measurement and system of structural angle, it is intended to solve in the prior art for the measurement method of myoarchitecture angle
The problems such as precision is low, and robustness is low and the degree of automation is low.
The technical proposal for solving the technical problem of the invention is as follows:
The method for automatic measurement of structural angle in a kind of musculature, wherein the described method includes:
Muscle ultrasound image is obtained in real time in contraction of muscle movement, and the muscle ultrasound image is pre-processed,
To enhance the image edge information of the muscle ultrasound image；
Call it is preset normalization Radon transform algorithm in the muscle ultrasound image fascia and muscle bundle region into
Row divides, and obtains the first angle in deep fascia and the muscle ultrasound image between preset trunnion axis；
Radon transform is normalized to the muscle bundle region, is extracted in Radon transform matrix for the shape on Euclidean space
It is weighted and averaged at multiple peak points of multi beam muscle fibre, and to the position and direction of all muscle fibres, obtains the flesh
The second angle in fiber and the muscle ultrasound image between preset trunnion axis；
First angle and second angle are subjected to read group total, obtain the structural angle in musculature,
The structural angle is muscle pinniform angle.
The method for automatic measurement of structural angle in the musculature, wherein the muscle ultrasound image is to use
Ultrasound scanner obtain image, the long axis of the probe of the ultrasound scanner vertically with muscle long axis direction.
The method for automatic measurement of structural angle in the musculature, wherein described to the muscle ultrasound image
It is pre-processed, includes: to enhance the image edge information of the muscle ultrasound image
Each salient region in the muscle ultrasound image is obtained, and calculates the histogram of each salient region
Figure, redistributes the image brightness values of each salient region, enhances the local detail and marginal information of image.
The method for automatic measurement of structural angle in the musculature, wherein described to call preset normalization thunder
Step on transformation algorithm in the muscle ultrasound image fascia and muscle bundle region carry out divide include:
Radon transform is normalized to the muscle ultrasound image with preset angle interval；
The peak point on Radon transform matrix is extracted, and centered on the position of the peak point, it is wide with the lines of fascia
Degree and angle fluctuation range are long and wide, acquisition objective matrix region；
In Radon transform matrix, will be centered on the peak point position, and with twice of the distance between fascia
Long, the width of matrix resets for the region that width is constituted；
In the objective matrix region, then multiple peak points are obtained, and is known using the position of peak point, directional information
Other fascia；
Above-mentioned process is repeated, detects a plurality of fascia, completes the division of fascia and muscle bundle region.
The method for automatic measurement of structural angle in the musculature, wherein the public affairs of the normalization Radon transform
Formula are as follows:
R (ρ, θ)=∫ ∫D(I (x, y)-mean (I)) δ (ρ-xcos θ-ysin θ) dxdy；
Wherein, NR (ρ, θ)=mapminmax (R (ρ, θ))；R (ρ, θ) represents the image after standard Radon transform,
Mean (I) represents the gray average of the image, and mapminmax (R (ρ, θ)) is represented matrix normalization between 0 and 1.
The method for automatic measurement of structural angle in the musculature, wherein the acquisition deep fascia and the flesh
The first angle in meat ultrasound image between preset trunnion axis includes:
In the target area matrix, the peak point of preset quantity is chosen, and with the brightness value of the peak point of selection work
For weight, the position and direction of fascia are weighted and averaged；
The average angle of trunnion axis in deep fascia and muscle ultrasound image is recorded, the average angle is first folder
Angle.
The method for automatic measurement of structural angle in the musculature, wherein the average weighted calculation formula
Are as follows:
Wherein,Represent the mean direction of all muscle fibres, θiRepresent the direction per a branch of muscle fibre, ωiIt represents per a branch of
The weight of muscle fibre.
The automatic measurement system of structural angle in a kind of musculature, wherein the system comprises:
Image obtains and enhances module, for obtaining muscle ultrasound image in real time in contraction of muscle moves, and to described
Muscle ultrasound image is pre-processed, to enhance the image edge information of the muscle ultrasound image；
First angle obtains module, for calling preset normalization Radon transform algorithm in the muscle ultrasound image
Fascia and muscle bundle region divided, and obtain in deep fascia and the muscle ultrasound image between preset trunnion axis
First angle；
Second angle obtains module, for Radon transform to be normalized to the muscle bundle region, extracts Radon transform square
Battle array on Euclidean space formed multi beam muscle fibre multiple peak points, and to the position and direction of all muscle fibres into
Row weighted average, obtains the second angle in the muscle fibre and the muscle ultrasound image between preset trunnion axis；
Angle read group total module obtains flesh for first angle and second angle to be carried out read group total
Structural angle in meat tissue, the structural angle are muscle pinniform angle.
The automatic measurement system of structural angle in the musculature, wherein the muscle ultrasound image is to use
Ultrasound scanner obtain image, the long axis of the probe of the ultrasound scanner vertically with muscle long axis direction.
The automatic measurement system of structural angle in the musculature, wherein first angle obtains module packet
Division and positioning submodule are included, the division is used for positioning submodule: with preset angle interval to the muscle ultrasound figure
As Radon transform is normalized；
The peak point on Radon transform matrix is extracted, and centered on the position of the peak point, it is wide with the lines of fascia
Degree and angle fluctuation range are long and wide, acquisition objective matrix region；
In Radon transform matrix, will be centered on the peak point position, and with twice of the distance between fascia
Long, the width of matrix resets for the region that width is constituted；
In the objective matrix region, then multiple peak points are obtained, and is known using the position of peak point, directional information
Other fascia, and detect a plurality of fascia, complete the division of fascia and muscle bundle region.
Beneficial effects of the present invention: the present invention passes through the muscle ultrasound image obtained in muscle contraction in real time, and right
Radon transform is normalized in pretreated image, can effectively eliminate image border effect, and it is highlighted to solve image diagonal
The problem of, keep the measurement robustness of the structural angle in muscle image stronger, accuracy is higher, and the present invention uses polymyarian
The average weighted algorithm of fiber can naturally smooth, robust, high automaticity accurately measure the structural angle in musculature
Degree, so that measurement result closer to real motion state, more can reflect the structure function of Products for Cooked Whole Muscle.
Detailed description of the invention
Fig. 1 is the process of the preferred embodiment of the method for automatic measurement of structural angle in musculature provided by the invention
Figure.
Fig. 2 is that the muscle ultrasound image in musculature provided by the invention in the method for automatic measurement of structural angle shows
It is intended to.
Fig. 3 is the specific flow chart of the method for automatic measurement of structural angle in musculature provided by the invention.
Fig. 4 be in musculature provided by the invention in the method for automatic measurement of structural angle to muscle ultrasound image
Enhancing front and back comparison diagram.
Fig. 5 is the increasing of muscle ultrasound image in the method for automatic measurement of structural angle in musculature provided by the invention
Image and its corresponding Radon transform matrix after strong.
Fig. 6 is to divide fascia and muscle bundle area in musculature provided by the invention in the method for automatic measurement of structural angle
The peak point schematic diagram extracted during domain.
Fig. 7 be in musculature provided by the invention in the method for automatic measurement of structural angle through normalize Radon transform
Muscle fibre schematic diagram after extraction.
Fig. 8 is the principle of work and power money figure of the automatic measurement system of structural angle in musculature provided by the invention.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer and more explicit, right as follows in conjunction with drawings and embodiments
The present invention is further described.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and do not have to
It is of the invention in limiting.
Muscle is the vital tissue for constituting human body, and major function is to generate the movement shunk and control body.Research hair
Existing, the mode that myoarchitecture is transmitted to tendon and bone to muscular strength has an important influence[1].Myoarchitecture angle, such as muscle plumage
Shape angle is the important indicator of skeletal muscle research.Myoarchitecture angle is related to the high strength of contraction of muscle, can help to cure
It is raw to understand muscular biomechanics characteristic, muscle function and pathological state are preferably assessed, is provided for clinical diagnosis and rehabilitation assessment
Effective foundation serves medical science of recovery therapy or sports science.However the composition of muscle is sufficiently complex, and it is dynamic how precisely to quantify muscle
Structure when state is shunk is the hot and difficult issue in motion function rehabilitation and sports medical science research.
Muscle ultrasonic imaging is noninvasive radiationless, inexpensive, the real-time display normal tissue of one kind and pathology musculature
Technology.The real-time Dynamic Graph of structural object variations when due to that can be measured under free position and provide contraction of muscle
Picture, two-dimensional ultrasonic image have been widely used in studying the change of morphosis in muscular movement, comment for clinical diagnosis and rehabilitation
Estimate and provides effective means.Muscle image is obtained using ultrasonic instrument and is analyzed and obtains the structural parameters of muscle, is commented with this
Estimate muscle function and pathological state.Structural angle in musculature is important and straight as one for assessing muscle function state
The parameter of sight, how naturally smooth, robust, to accurately measure myoarchitecture angle most important.
Currently, main using the method that image processing techniques carries out automatic measurement to angle structural in muscle ultrasound image
There are three types of: the first is the signature tracking based on multiple ultrasound images, and second is the feature detection based on individual ultrasound image,
The third is the end-to-end detection based on deep learning.
The method of signature tracking refers to sketches out area-of-interest manually on first frame image, is then calculated using tracking
Method, such as Lucas-Kanade optical flow algorithm (the light stream algorithm for estimating that Lucas-Kanade optical flow algorithm is a kind of two frame differences) or
Cross correlation algorithm dynamically tracks selected target in adjacent interframe.Signature tracking in ultrasound image is challenging, because
The target tracked in muscle deformation, speckle noise and area-of-interest must be handled for it to occur in appearance or intensity
The problems such as significant changes.Currently, although certain track algorithms show well in certain particular tasks, it can be because of sequential chart
Cumulative tracking error is shown the problems such as the inhomogeneous deformation of area-of-interest, noise jamming or even disappearance as between；
And track algorithm needs to choose the tracking position of first frame manually, and this automanual interactive mode can be passed through due to operator
The difference tested and there is deviation.
The method of feature detection such as fascia and muscle fibre, in the case where linearly, is led to assuming that structural target
It crosses in muscle ultrasound image and positions these linear structures to identify structural target.On muscle ultrasound image, fascia is in company
Continuous high echo distribution, and muscle fibre is usually with linear structure uneven distribution.Come by using Hough transformation or Radon transform
Muscle fibre is detected, the measurement of myoarchitecture angle may be implemented.Although general characteristic detection method can be become by Hough
It changes or Radon transform determines the representative beam to but on the ultrasound image, speckle noise, the appearance of intramuscular blood vessel are past
Toward the important feature of meeting masking structures target, the difficulty of the structural angle of precise measurement is increased.
The detection method of deep learning refers to framework neural network model, by learning in clearly defined region
Structural target information predicts the direction of local structure target.Although deep learning method is applied in region-wide Skeletal Muscle
Performance in machine direction, within an acceptable error range, but due to the characteristic of its data-driven, model needs to train for performance
Mass data, to power resource is calculated, the training time requires high.And the technology is not yet mature at present, to myoarchitecture angle
Dynamic measurement still will appear biggish deviation.
To solve the above-mentioned problems, the present embodiment provides a kind of method for automatic measurement sides of structural angle in musculature
Method, it is specific as shown in fig. 1, method includes the following steps:
Step S100, obtain muscle ultrasound image in real time in contraction of muscle movement, and to the muscle ultrasound image into
Row pretreatment, to enhance the image edge information of the muscle ultrasound image；
Step S200, call preset normalization Radon transform algorithm to the fascia and flesh in the muscle ultrasound image
Beam region is divided, and obtains the first angle in deep fascia and the muscle ultrasound image between preset trunnion axis；
Step S300, Radon transform is normalized to the muscle bundle region, extracted in Radon transform matrix in Europe
Family name spatially forms multiple peak points of multi beam muscle fibre, and is weighted and averaged to the position and direction of all muscle fibres,
Obtain the second angle in the muscle fibre and the muscle ultrasound image between preset trunnion axis；
Step S400, first angle and second angle are subjected to read group total, obtain the knot in musculature
Structure angle, the structural angle are muscle pinniform angle.
The muscle ultrasound image in muscle contraction is obtained by implementing in the present embodiment, and to pretreated image
Radon transform is normalized, image border effect can be effectively eliminated, solves the problems, such as that image diagonal is highlighted, makes muscle figure
The measurement robustness of structural angle as in is stronger, and accuracy is higher, and the present invention is average weighted using polymyarian fiber
Algorithm can naturally smooth, robust, high automaticity accurately measure the structural angle in musculature, so that measurement knot
Fruit more can reflect the structure function of Products for Cooked Whole Muscle closer to real motion state.
Specifically, the present embodiment is first when contraction of muscle moves, ultrasound image caused by the contraction of muscle of record, when
So, it further includes the letter such as output torque value or myoelectricity, joint angles that signal recorded in this process, which not only only has ultrasound image,
Number dynamic change.The instrument and method of record ultrasound image and output signal have very much, preferred 10MHz electronics in the present embodiment
The Real-time B-Mode Ultrasound scanner of linear array probe obtains muscle ultrasound image.In the specific implementation, the long axis of ultrasonic probe should hang down
Directly in muscle long axis direction, (measured from anterior superior spine to kneecap upper limb) apart from knee joint distal side 40%.It is fixed that ultrasonic probe passes through
The Foam Container with fixing belt for setting up meter is fixed, and during contraction of muscle using a large amount of ultrasound gels to ensure to pop one's head in
Acoustics between skin couples.And it can adjust ultrasonic probe to optimize the contrast of muscle bundle in ultrasound image, and to position
It is marked to ensure to pop one's head in and be placed on identical position every time, improves the accuracy that image obtains.
It is muscle ultrasound image in Fig. 2 referring to Fig. 2, includes deep fascia, shallow muscle in the muscle layer of skeletal muscle shown in Fig. 2
Film and muscle package region can draw muscle bundle line L1 and deep fascia line according to the direction of the orientation of muscle fibre and deep fascia
L2, the angle theta between two lines are defined as pinniform angle, the structural angle as measured required for the present invention.Specifically, originally
Measurement method in embodiment is as shown in Figure 3, pre-processes first to muscle ultrasound image, enhances image edge information,
To help to divide deep, fascia superficialis and muscle bundle region.Then, the present embodiment is using normalization Radon transform to depth, fascia superficialis
It is accurately positioned and is divided, the angle being calculated between deep fascia and horizontal line (X-axis i.e. on muscle ultrasound image) is θ
1 (the first angle).Then, Radon transform is normalized to the muscle bundle region marked off in we again, extracts Radon transform
A large amount of peak points in matrix form multi beam muscle fibre on Euclidean space, add to the direction and position of all muscle fibres
Weight average, recording its angle between horizontal line ((X-axis i.e. on muscle ultrasound image)) is θ 2 (the second angle), passes through formula
Angle theta 1 and 2 read group total of angle theta can be measured to the pinniform angle θ (θ=θ 1+ θ 2) of the muscle ultrasound image.
Further, since muscle ultrasound image includes fascia, muscle bundle textural characteristics and noise information.Important texture is special
The interference vulnerable to high speckle noise and intramuscular blood vessel is levied, the difficulty that each tissue is accurately positioned is caused to increase.Therefore, the present embodiment
It needs to carry out enhancing processing to muscle ultrasound image.Preferably, the present embodiment is equal using the self-adapting histogram of limitation contrast
It weighs (Contrast Limited Adaptive Histogram Equalization, CLAHE), CLAHE is a kind of improvement figure
The image processing techniques of image contrast.It specifically includes and obtains each salient region in the muscle ultrasound image, and calculate
The histogram of each salient region redistributes the image brightness values of each salient region, enhances the part of image
Details and marginal information.Meanwhile each neighborhood of pixels on image can degree of comparing limitation, overcome noise jamming,
As shown in figure 4, a is original muscle ultrasound image in Fig. 4, b is the enhanced muscle ultrasound image of CLAHE.In the present embodiment,
CLAHE can effectively inhibit noise, reduce error caused by noise, enhance muscle bundle textural characteristics, be conducive to promote Lei Dengbian
Change the positioning and recognition capability to structural target.
Specifically, on muscle ultrasound image, fascia is usually expressed as continuous high echo zone, and direction is close to zero
Degree, and muscle fibre is usually expressed as the linear structure of uneven distribution, direction also has mark that can follow.Therefore, for continuity muscle
Film and isotropism muscle fibre, the present embodiment are detected using Radon transform.The Radon transform of standard is under theorem in Euclid space
Formula are as follows:
R (ρ, θ)=∫ ∫DI (x, y) δ (ρ-xcos θ-ysin θ) dx dy
Wherein, I (x, y) represents the image grayscale in the position (x, y), and δ is Dirac delta function, and ρ is straight line to picture centre
Distance, θ be x-axis and line angle, D is image lattice.The Radon transform of standard represents whole image plane in its projection
Gray integration on direction because the peak point on Radon transform matrix can characterize the characteristic of straight line, and is widely used in straight
The extraction of line and the identification on boundary.But since on different projecting directions, integration path lengths are different, it is easy to produce edge effect
It answers, as shown in Figure 5, can not determine that direction representated by which peak point is fascia direction.In order to eliminate edge effect, this
Embodiment proposes a kind of new normalization Radon transform:
R (ρ, θ)=∫ ∫D(I (x, y)-mean (I)) δ (ρ-xcos θ-ysin θ) dxdy
NR (ρ, θ)=mapminmax (R (ρ, θ))；
Wherein, R (ρ, θ) represents the image after standard Radon transform, and mean (I) represents the gray average of the image,
Mapminmax (R (ρ, θ)) is represented matrix normalization between 0 and 1.First by subtracting original image in the present embodiment
Image grayscale mean value solves the problems, such as that diagonal line generally highlights in Radon transform matrix, then according to the elder generation of fascia direction scope
Knowledge is tested, Radon transform is normalized to image with preset angle interval (such as 0.1 degree).In order to accurately divide fascia with
Muscle bundle region, the present embodiment also need the division that fascia and muscle bundle region are completed by following steps, comprising:
The peak point on Radon transform matrix is extracted, and centered on the position of the peak point, it is wide with the lines of fascia
Degree and angle fluctuation range are long and wide, acquisition objective matrix region；
In Radon transform matrix, will be centered on the peak point position, and with twice of the distance between fascia
Long, the width of matrix resets for the region that width is constituted；
In the objective matrix region, then multiple peak points are obtained, and is known using the position of peak point, directional information
Other fascia；
Above-mentioned process is repeated, detects a plurality of fascia, completes the division of fascia and muscle bundle region.
The present embodiment through the above steps, can accurately mark off the fascia in muscle ultrasound image and muscle bundle region,
As shown in Figure 6, a figure is the fascia peak point (point of black in Fig. 6) extracted in Fig. 6, and b figure is the corresponding straight line of peak point,
Realize the accurate positioning of fascia Yu muscle bundle region.
Further, thunder is mapped to since the brightness value on Radon transform matrix represents each straight line on original image
Step on accumulation results spatially.Numerical value is bigger, and it is bigger to illustrate that inversion gains a possibility that Euclidean space is straight line.Therefore, originally
Invention chooses the peak point (such as 50 peak points) of predetermined quantity in objective matrix region using this information, each with them
From brightness value position and direction are weighted and averaged as weight, and record deep fascia and horizontal line (X-axis in image)
Between average angle be θ 1.Average weighted calculation formula is as follows:
Wherein,Represent the mean direction of all muscle fibres, θiRepresent the direction per a branch of muscle fibre, ωiIt represents per a branch of
The weight of muscle fibre.The present embodiment can accurately identify the predominant direction of fascia, realize the automatic of depth, fascia superficialis and muscle bundle region
It divides.
Further, the present embodiment can also be spaced according to the priori knowledge of muscle fibre direction scope, and at an angle
(such as 0.1 degree) is normalized Radon transform to the muscle bundle region marked off, extracts multiple peaks in Radon transform matrix
It is worth point (such as 1000 peak values), forms multi beam muscle fibre on Euclidean space, as shown in fig. 7, a in Fig. 7 is the flesh fibre extracted
It ties up peak point (point of black in Fig. 7), b is straight line corresponding to peak point.Then to the position and direction of all muscle fibres into
Row weighted average, and recording its angle between horizontal line (X-axis in image) is θ 2.Then θ 1 is being added with θ 2, i.e.,
The muscle pinniform angle that each frame muscle ultrasound image can be accurately calculated, i.e., the structural angle in musculature.
Using polymyarian fiber Weighted Average Algorithm processing ultrasound image come dynamic studies myoarchitecture angle in the present embodiment
The variation of degree and related Morphological parameter (such as muscle thickness, muscle fibre angle, muscle bundle length, muscle physiological cross-sectional area),
The measurement accuracy of structural angle is effectively increased, robustness is high.Structure in a kind of musculature provided through this embodiment
Property angle method for automatic measurement, the interference of high speckle noise and intramuscular blood vessel can be overcome, effectively divide fascia and muscle bundle area
Domain realizes that the full-automatic of structural angle dynamic change accurately measures in muscle contraction.Compared with existing measurement method,
The measurement result of the present embodiment and the result that expert delineates manually are more identical, higher with muscular strength correlation, structural angle dynamic
Curve is naturally smooth；And algorithm can be applicable on the different types of data set of multiple groups, and robustness is stronger, does not need to manually adjust
Accurately measuring for structural angle can be completed in parameter, and the degree of automation is higher.
Based on the above embodiment, the present invention also provides a kind of automatic measurement systems of structural angle in musculature, such as
Shown in Fig. 8, which includes: that image obtains and enhancing module 810, the first angle acquisition module 820, the second angle acquisition mould
Block 830, angle read group total module 840.
Specifically, image obtains and enhances module 810, for obtaining muscle ultrasound figure in real time in contraction of muscle moves
Picture, and the muscle ultrasound image is pre-processed, to enhance the image edge information of the muscle ultrasound image；
First angle obtains module 820, for calling preset normalization Radon transform algorithm to the muscle ultrasound figure
Fascia and muscle bundle region as in are divided, and obtain in deep fascia and the muscle ultrasound image preset trunnion axis it
Between the first angle；
Second angle obtains module 830, for Radon transform to be normalized to the muscle bundle region, extracts Radon transform
For forming multiple peak points of multi beam muscle fibre on Euclidean space in matrix, and to the position and direction of all muscle fibres
It is weighted and averaged, obtains the second angle in the muscle fibre and the muscle ultrasound image between preset trunnion axis；
Angle read group total module 840 is obtained for first angle and second angle to be carried out read group total
Structural angle in musculature, the structural angle are muscle pinniform angle.
Preferably, the Real-time B-Mode Ultrasound scanner of the preferred 10MHz electronics linear array probe of the present embodiment is ultrasonic to obtain muscle
Image.In the specific implementation, the long axis of ultrasonic probe should be perpendicular to muscle long axis direction, apart from knee joint distal side 40% (from ilium
Ant sup to kneecap upper limb measures).
Preferably, the first angle acquisition module 820 includes division and positioning submodule in the present embodiment, described to divide and determine
Bit submodule is used for: Radon transform is normalized to the muscle ultrasound image with preset angle interval；Extract Lei Dengbian
The peak point on matrix is changed, and centered on the position of the peak point, with the line thickness of fascia and angle fluctuation range
It is long and wide, acquisition objective matrix region；It, will be centered on the peak point position, and with fascia in Radon transform matrix
The distance between twice be length, the width of matrix is the wide region clearing constituted；In the objective matrix region, then obtain
Multiple peak points are taken, and identify fascia using the position of peak point, directional information, and detect a plurality of fascia, complete fascia
With the division in muscle bundle region.
The present embodiment by real time obtain muscle contraction in muscle ultrasound image, and to pretreated image into
Row normalization Radon transform, can effectively eliminate image border effect, solve the problems, such as that image diagonal is highlighted, make muscle image
In structural angle measurement robustness it is stronger, accuracy is higher, and the present invention use the average weighted calculation of polymyarian fiber
Method can naturally smooth, robust, high automaticity accurately measure the structural angle in musculature, so that measurement result
Closer to real motion state, the structure function of Products for Cooked Whole Muscle more can reflect.
In conclusion the present invention discloses structural angle method for automatic measurement and system in a kind of musculature, the side
Method includes: to obtain muscle ultrasound image in real time in contraction of muscle movement, and pre-process to the muscle ultrasound image, with
Enhance the image edge information of the muscle ultrasound image；Call preset normalization Radon transform algorithm to the muscle ultrasound
Fascia and muscle bundle region in image are divided, and obtain preset trunnion axis in deep fascia and the muscle ultrasound image
Between the first angle；Radon transform is normalized to the muscle bundle region, is extracted in Radon transform matrix in Euclidean
Multiple peak points of multi beam muscle fibre are spatially formed, and the position and direction of all muscle fibres are weighted and averaged, are obtained
Take the second angle in the muscle fibre and the muscle ultrasound image between preset trunnion axis；By first angle and institute
It states the second angle and carries out read group total, obtain the structural angle in musculature, the structural angle is muscle pinniform angle.
The present invention can naturally smooth, robust, automatically measure structural angle in musculature so that measurement result is closer
True motion state more can reflect the structure function of muscle.
It should be understood that the application of the present invention is not limited to the above for those of ordinary skills can
With improvement or transformation based on the above description, all these modifications and variations all should belong to the guarantor of appended claims of the present invention
Protect range.
Claims (10)
1. the method for automatic measurement of structural angle in a kind of musculature, which is characterized in that the described method includes:
Muscle ultrasound image is obtained in real time in contraction of muscle movement, and the muscle ultrasound image is pre-processed, to increase
The image edge information of the strong muscle ultrasound image；
Call it is preset normalization Radon transform algorithm in the muscle ultrasound image fascia and muscle bundle region draw
Point, and obtain the first angle in deep fascia and the muscle ultrasound image between preset trunnion axis；
Radon transform is normalized to the muscle bundle region, is extracted more for being formed on Euclidean space in Radon transform matrix
Multiple peak points of beam muscle fibre, and the position and direction of all muscle fibres are weighted and averaged, obtain the muscle fibre
With the second angle in the muscle ultrasound image between preset trunnion axis；
First angle and second angle are subjected to read group total, obtain the structural angle in musculature, it is described
Structural angle is muscle pinniform angle.
2. the method for automatic measurement of structural angle in musculature according to claim 1, which is characterized in that the flesh
Meat ultrasound image be using ultrasound scanner obtain image, the long axis of the probe of the ultrasound scanner vertically with muscle long axis
Direction.
3. the method for automatic measurement of structural angle in musculature according to claim 1, which is characterized in that described right
The muscle ultrasound image is pre-processed, and includes: to enhance the image edge information of the muscle ultrasound image
Each salient region in the muscle ultrasound image is obtained, and calculates the histogram of each salient region, weight
The image brightness values of each salient region are newly distributed, the local detail and marginal information of image are enhanced.
4. the method for automatic measurement of structural angle in musculature according to claim 1, which is characterized in that the tune
With it is preset normalization Radon transform algorithm in the muscle ultrasound image fascia and muscle bundle region carry out divide include:
Radon transform is normalized to the muscle ultrasound image with preset angle interval；
Extract the peak point on Radon transform matrix, and centered on the position of the peak point, with the line thickness of fascia with
And angle fluctuation range is long and wide, acquisition objective matrix region；
It will be length, square centered on the peak point position, and with twice of the distance between fascia in Radon transform matrix
The width of battle array resets for the region that width is constituted；
In the objective matrix region, then multiple peak points are obtained, and identifies muscle using the position of peak point, directional information
Film；
Above-mentioned process is repeated, detects a plurality of fascia, completes the division of fascia and muscle bundle region.
5. the method for automatic measurement of structural angle in musculature according to claim 4, which is characterized in that described to return
One changes the formula of Radon transform are as follows:
R (ρ, θ)=∫ ∫D(I (x, y)-mean (I)) δ (ρ-xcos θ-ysin θ) dxdy；
Wherein, NR (ρ, θ)=mapminmax (R (ρ, θ)), R (ρ, θ) represent the image after standard Radon transform, mean
(I) gray average of the image is represented, mapminmax (R (ρ, θ)) is represented matrix normalization between 0 and 1.
6. the method for automatic measurement of structural angle in musculature according to claim 4, which is characterized in that described to obtain
The first angle in deep fascia and the muscle ultrasound image between preset trunnion axis is taken to include:
In the target area matrix, the peak point of preset quantity is chosen, and using the brightness value of the peak point of selection as power
Weight, is weighted and averaged the position and direction of fascia；
The average angle of trunnion axis in deep fascia and muscle ultrasound image is recorded, the average angle is first angle.
7. the method for automatic measurement of structural angle in musculature according to claim 6, which is characterized in that described to add
The calculation formula of weight average are as follows:
Wherein,Represent the mean direction of all muscle fibres, θiRepresent the direction per a branch of muscle fibre, ωiIt represents fine per a branch of flesh
The weight of dimension.
8. the automatic measurement system of structural angle in a kind of musculature, which is characterized in that the system comprises:
Image obtains and enhances module, for obtaining muscle ultrasound image in real time in contraction of muscle moves, and to the muscle
Ultrasound image is pre-processed, to enhance the image edge information of the muscle ultrasound image；
First angle obtains module, for calling preset normalization Radon transform algorithm to the muscle in the muscle ultrasound image
Film and muscle bundle region are divided, and obtain in deep fascia and the muscle ultrasound image between preset trunnion axis first
Angle；
Second angle obtains module, for Radon transform to be normalized to the muscle bundle region, extracts in Radon transform matrix
For forming multiple peak points of multi beam muscle fibre on Euclidean space, and the position and direction of all muscle fibres are added
Weight average obtains the second angle in the muscle fibre and the muscle ultrasound image between preset trunnion axis；
Angle read group total module obtains muscle groups for first angle and second angle to be carried out read group total
Structural angle in knitting, the structural angle are muscle pinniform angle.
9. the automatic measurement system of structural angle in musculature according to claim 8, which is characterized in that the flesh
Meat ultrasound image be using ultrasound scanner obtain image, the long axis of the probe of the ultrasound scanner vertically with muscle long axis
Direction.
10. the automatic measurement system of structural angle in musculature according to claim 8, which is characterized in that described
It includes division and positioning submodule that first angle, which obtains module, and the division and positioning submodule are used for: between preset angle
Every Radon transform is normalized to the muscle ultrasound image；
Extract the peak point on Radon transform matrix, and centered on the position of the peak point, with the line thickness of fascia with
And angle fluctuation range is long and wide, acquisition objective matrix region；
It will be length, square centered on the peak point position, and with twice of the distance between fascia in Radon transform matrix
The width of battle array resets for the region that width is constituted；
In the objective matrix region, then multiple peak points are obtained, and identifies muscle using the position of peak point, directional information
Film, and detect a plurality of fascia, complete the division of fascia and muscle bundle region.
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