CN104252708B - A kind of x-ray chest radiograph image processing method and system - Google Patents
A kind of x-ray chest radiograph image processing method and system Download PDFInfo
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Abstract
The present invention is applied to technical field of image processing there is provided a kind of x-ray chest radiograph image processing method and system, and this method includes：Obtain the positional information and the positional information of backbone of body's border in x-ray chest radiograph；According to the positional information of the body's border, the body region in x-ray chest radiograph is determined, and relevant matches are carried out by the multiple body marker templates and the body region being pre-created, the image outside correlation highest body marker template is set to zero to obtain initial pictures；Bone images are extracted from the initial pictures by medium filtering thresholding algorithm；The Bone images are divided into by two parts in left and right according to the positional information of the backbone；Relevant matches are carried out to obtain dependency graph picture with described two parts in left and right respectively by the multiple left and right rib templates being pre-created, and the dependency graph picture is divided, and obtain the positional information of left and right rib in x-ray chest radiograph.Fast and accurately the rib in x-ray chest radiograph can be positioned by the present invention.
Description
Technical field
The invention belongs to technical field of image processing, more particularly to a kind of x-ray chest radiograph image processing method and system.
Background technology
X-ray chest radiograph refers to pass through chest by X-ray, is projected in the image formed on film, is a routine physical examination
Inspection project.In checking process, it usually needs the rib part in x-ray chest radiograph is positioned and split, so as to rib
The disease of bone and lung makes diagnosis.
In the prior art, dividing processing is generally carried out to the rib part in x-ray chest radiograph using Gauss curved threshold method.
However, for the poor image of projection quality, especially to disappearance, the only visible image in two ends, Gauss in the middle part of rib in image
Curved surface threshold method is unable to reach Expected Results, in the extraction of Bone images, and a large amount of Bone images are not extracted by out.And utilize
Least square method is fitted to rib, then too relies on the selection to rib edge sampled point, in x-ray chest radiograph image, by
In the complexity of image, sampled point is chosen and is difficult, it is easy to cause positioning and segmentation errors.Yue propose based on Hough transformation
Rib dividing method, its every image procossing is time-consuming to reach more than ten minutes, takes longer, and treatment effeciency is relatively low.
The content of the invention
The embodiment of the present invention is to provide a kind of x-ray chest radiograph image processing method, with fast and accurately in x-ray chest radiograph
Rib positioned.
The first aspect of the embodiment of the present invention includes there is provided a kind of x-ray chest radiograph image processing method, methods described：
Obtain the positional information and the positional information of backbone of body's border in x-ray chest radiograph；
According to the positional information of the body's border, the body region in the x-ray chest radiograph is determined, and by being pre-created
Multiple body marker templates and the body region carry out relevant matches, the image outside correlation highest body marker template is set to
Zero to obtain initial pictures；
Bone images are extracted from the initial pictures by medium filtering thresholding algorithm；
The Bone images are divided into by two parts in left and right according to the positional information of the backbone；
By multiple left and right rib templates for being pre-created carried out respectively with described two parts in left and right relevant matches with
Dependency graph picture is obtained, and the dependency graph picture is divided, the positional information of left and right rib in x-ray chest radiograph is obtained.
The second aspect of the embodiment of the present invention includes there is provided a kind of x-ray chest radiograph image processing system, the system：
Location information acquiring unit, for obtaining the positional information of body's border and the positional information of backbone in x-ray chest radiograph；
Initial pictures acquiring unit, for the position letter of the body's border obtained according to the location information acquiring unit
Breath, determines the body region in the x-ray chest radiograph, and carry out by the multiple body marker templates and the body region being pre-created
Relevant matches, the image outside correlation highest body marker template is set to zero to obtain initial pictures；
Bone images acquiring unit, for extracting frame body plan from the initial pictures by medium filtering thresholding algorithm
Picture；
The Bone images are divided into two portions in left and right by image division unit for the positional information according to the backbone
Point；
Rib position determination unit, for multiple left and right rib templates by being pre-created respectively with it is described left and right two
Part carries out relevant matches to obtain dependency graph picture, and the dependency graph picture is divided, and obtains left in x-ray chest radiograph
The positional information of right rib.
The beneficial effect that the embodiment of the present invention exists compared with prior art is：The embodiment of the present invention passes through medium filtering threshold
Value-based algorithm replaces Gauss curved thresholding algorithm, when picture quality is preferable, and rib segmentation effect is calculated close to Gauss curved threshold value
Method, when picture quality is poor, rib part still can be obtained as far as possible, the universality of algorithm is improved.In rib positioning
On, by the body marker template and rib template of establishment carry out relevant matches and independent of in x-ray chest radiograph image rib it is several
What shape and position distribution, the size of template is adjusted according to the information of image itself, the robustness of algorithm is improved.Pass through correlation
Property matching rib is positioned, compared with Hough transformation, greatly reduce the processing time of image（About 50 seconds）, realize rib
The quick positioning of bone.
Brief description of the drawings
Technical scheme in order to illustrate the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art
In required for the accompanying drawing that uses be briefly described, it should be apparent that, drawings in the following description are only some of the present invention
Embodiment, for those of ordinary skill in the art, without having to pay creative labor, can also be according to these
Accompanying drawing obtains other accompanying drawings.
Fig. 1 is the schematic flow sheet for the x-ray chest radiograph image processing method that one embodiment of the invention is provided；
Fig. 2 is position and the exemplary plot of backbone position of body's border in the x-ray chest radiograph that one embodiment of the invention is provided；
Fig. 3 is the exemplary plot for the body marker template that one embodiment of the invention is provided；
Fig. 4 is the exemplary plot for the body marker template matching that one embodiment of the invention is provided；
Fig. 5 is the exemplary plot for the Bone images that one embodiment of the invention is provided；
Fig. 6 is the exemplary plot for the rib template that one embodiment of the invention is provided；
7a in Fig. 7 is the exemplary plot for the left rib dependency graph picture that one embodiment of the invention is provided, and 7b is the present invention one
The exemplary plot for the right rib dependency graph picture that embodiment is provided；
Fig. 8 be one embodiment of the invention provide first time Threshold segmentation after rib matched position exemplary plot；
Fig. 9 be one embodiment of the invention provide second of Threshold segmentation after rib matched position exemplary plot；
Figure 10 is the exemplary plot for the rib best angle matching that one embodiment of the invention is provided；
Figure 11 is the exemplary plot that the rib region that one embodiment of the invention is provided is divided；
12a in Figure 12 is the poor x-ray chest radiograph image of shooting quality that one embodiment of the invention is provided, and Figure 12 b are these
The Bone images that the Gauss curved thresholding algorithm of embodiment offer is obtained are invented, Figure 12 c are the present embodiment medium filtering threshold values
The Bone images that algorithm is obtained；
Figure 13 is the structural representation for the x-ray chest radiograph image processing system that another embodiment of the present invention is provided.
Embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, it is right below in conjunction with drawings and Examples
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
In order to illustrate technical solutions according to the invention, illustrated below by specific embodiment.
Fig. 1 shows the implementation process for the x-ray chest radiograph image processing method that one embodiment of the invention is provided, this method process
Details are as follows：
In step S101, the positional information and the positional information of backbone of body's border in x-ray chest radiograph are obtained.
Exemplary, the present embodiment is carried out true by watershed algorithm to the position of body's border in x-ray chest radiograph and backbone
It is fixed.It should be noted that why the present embodiment selects watershed algorithm, it is because the basic thought of watershed algorithm is to scheme
As regarding that the gray value of each pixel in the topological landforms in geodesy, image represents the height above sea level of the point as, each
Local minimum and its influence area are referred to as reception basin, and the border of reception basin then forms watershed, and by gradient magnitude image
Split as the input picture of watershed algorithm.Based on this, the present embodiment will it is smooth after image（15 × 15 medium filterings
Handle the image obtained）Instead of input picture (I of the gradient magnitude image as watershed algorithmsmooth), the advantage so handled
The over-segmentation phenomenon of watershed algorithm is reduction of, while obvious body's border and backbone in x-ray chest radiograph can be obtained
Position.
Watershed algorithm output image in addition to comprising required body's border and backbone position, also exist rib,
The border interference of the transverse direction bone such as clavicle, the present embodiment also filters out the dry of horizontal boundary by the opening operation in vertical direction
Disturb, only retain body's border and the backbone position of longitudinal direction.3 maximum connected domains of longitudinal length are extracted, and according to position of centre of gravity
Abscissa judge right boundary and the backbone position of body, the position of its center of gravity is respectively from left to right body left margin, ridge
Post and body right margin（As shown in Figure 2）.
In step s 102, according to the positional information of the body's border, the body region in the x-ray chest radiograph is determined,
And relevant matches are carried out by the multiple body marker templates and the body region being pre-created, by correlation highest body mould
Image outside plate is set to zero to obtain initial pictures.
Because different personal shape is different, the present embodiment is according to the body shape of people（The especially journey of becoming thin of shoulder
Degree）Create M（M is the integer more than 0, M=3 preferably）Individual body marker template（As shown in Figure 3）, and according to the body's border
Positional information calculation obtains shoulder width, according to the shoulder width, the side that the M body marker template of establishment is passed through into scaling
Formula carries out relevant matches with the body region（As shown in Figure 4）, correlation highest body marker template is obtained, and by correlation
Image outside highest body marker template is set to zero to obtain initial pictures.
Wherein, the relevant matches calculation formula is：
f（X, y) represent original image（When body marker template is matched, the artwork is the body region image；In rib mould
When plate is matched, the artwork is left and right Bone images）, w（X, y) matching template is represented, F (u, v) represents f（X, y) Fourier
Conversion, H (u, v) represents w（X, y) Fourier transformation, "." correlation operation is represented, " * " represents complex conjugate.
Image outside correlation highest body marker template is set to zero by the present embodiment, only the image inside reservation, it is to avoid
The interference that bone outside skull, clavicle and other bodies is positioned to rib.
In step s 103, Bone images are extracted from the initial pictures by medium filtering thresholding algorithm.
Particularly, minor radius median filter process is carried out to the initial pictures and obtains smoothed image Ismooth；
Large radius median filter process is carried out to the initial pictures（Image is after large radius median filter process, figure
The information that the details of picture includes rib will be filtered out）, and by the image I after large radius median filter processremove detailMake
The smoothed image is split for threshold plane, i.e. Idetail=|Ismooth-Iremove detail|, obtain Bone images
Idetail, as shown in Figure 5.IdetailThe rib information of the overwhelming majority is contained in image, while eliminating uneven background；
According to predetermined threshold value（Preferably 3）Binary conversion treatment is carried out to the Bone images, detailed process example is as follows, if
Brightness value is Gray, and the Gray pixels for being more than or equal to threshold value 3 are placed in into white, and the Gray pixels for being less than threshold value 3 are put
In black.
In step S104, the Bone images are divided into by two parts in left and right according to the positional information of the backbone；
In step S105, carried out respectively with described two parts in left and right by the multiple left and right rib templates being pre-created
Relevant matches are divided with obtaining dependency graph picture to the dependency graph picture, obtain left and right rib in x-ray chest radiograph
Positional information.
The present embodiment is before relevant matches are carried out to the rib head portrait, it is necessary to will according to the positional information of the backbone
The Bone images are divided into left and right two parts, i.e. left and right Bone images, and by the multiple left and right rib templates being pre-created
（As shown in Figure 6）Relevant matches are carried out with described two parts in left and right respectively by way of scaling and/or rotating, phase is obtained
Closing property image（As shown in 7a, 7b in Fig. 7, wherein Fig. 7 a are left rib dependency graph picture, and Fig. 7 b are right rib dependency graph
Picture）.
It should be noted that the present embodiment is pre-created multiple left and right rib templates according to the average shape of rib.And root
According to the positional information of the body's border obtained before, estimate the width of rib, left and right rib template is zoomed to and the rib
Width identical size.Because the angle of inclination of rib in different templates is different, this implementation is needed to the left and right rib template
The rotation of 0~15 ° of progress, carries out relevant matches, acquisition is related by each postrotational left and right rib template with Bone images
Property image.
Further, the present embodiment also includes：
With the N of the maximum related value obtained in phase relation matching process（It is preferred that N=0.7）Times for thresholding to the correlation
Image is divided, and obtains one or more rib matched positions（As shown in Figure 8）, the N is normal more than zero but less than 1
Number.As shown in figure 8, each connected domain represents one or more rib matched positions.Preferably, the present embodiment in order to split away from
From close rib matched position, with 0.7 times of the maximum related value in connected domain for thresholding, each connected domain is carried out again
Threshold segmentation, the rib matched position separated（As shown in Figure 9）, each connected domain only represents an independent rib in Fig. 9
Matched position.It is rib matched position coordinate, i.e. rib template to take the coordinate in each connected domain where maximum related value
Starting point coordinate.Starting point coordinate is limited in the range of certain abscissa, and the starting point coordinate of left rib is limited in a body left side
Border 20 pixels of a left side are in right 50 pixel coverage, and the starting point coordinate of right rib is limited in backbone 20 pixels of a left side to right 50 pixel model
In enclosing.Simultaneously to avoid the multiple matching problem of same rib, the close coordinate of starting point ordinate is taken by preset rules
Give up, the preset rules can be：1）Longitudinal average headway of starting point coordinate is calculated, if the longitudinal pitch in the presence of 2 points is less than
The half of average headway, then depending on there is any to need to reject in this 2 points, but except the starting point of first and second rib；2）Respectively
Calculate 1）Described in 2 points with nearest starting point（Do not include at this 2 points）The distance between, retain and the nearest starting point
Point in larger distance, rejects point in small distance.Complete after Weeding, by remaining starting point coordinate and postrotational rib
Template coordinate is added as rib matched position.
Preferably, the present embodiment constructs to select the anglec of rotation best with the Bone images matching effect
One is weighed the whether optimal parameter of angle, i.e.,Wherein left rib K span is 0.8
The constant of≤K≤1.2, L span is the constant of 0.02≤L≤0.03, K=1, L=0.025 preferably；Right rib K's takes
It is worth the constant that scope is 0.8≤K≤1.2, L span is the constant of 0.8≤L≤1.2, K=1, L=1 preferably.In this reality
Apply in example, parameter Z linear degree is better, illustrate that the position distribution of rib in Bone images is distributed closer to experience.This implementation
Example selects optimal matching angle by calculating the linear degree of parameter Z under each anglec of rotation（As shown in Figure 10）.
Further, in order to ensure that each region only has a rib, the present embodiment also includes：
The center line of adjacent rib template matches position is obtained, and according to the center line, goes out to make by least square fitting
For the conic section in rib region line of demarcation（As shown in figure 11）.
The beneficial effect that the embodiment of the present invention exists compared with prior art is：（1）Image after will be smooth is used as a point water
The input picture of ridge algorithm obtains the positional information of body's border and the positional information of backbone in x-ray chest radiograph, can effectively reduce
The over-segmentation phenomenon of watershed algorithm, while the positional information of obvious body's border and backbone in x-ray chest radiograph can be obtained；
（2）Gauss curved thresholding algorithm is replaced by medium filtering thresholding algorithm, when picture quality is preferable, rib segmentation effect is approached
In Gauss curved thresholding algorithm, when picture quality is poor, rib part still can be obtained as far as possible, the general of algorithm is improved
Adaptive, in figure 12 it can be seen that compared with Gauss curved thresholding algorithm, the medium filtering thresholding algorithm of the present embodiment is in processing
Had a clear superiority during the x-ray chest radiograph image of shooting quality difference, Figure 12 c are more more complete than what Figure 12 b Bone images were preserved, press down simultaneously
The interference of its hetero-organization of the body interior such as backbone is made, wherein Figure 12 a are the poor x-ray chest radiograph images of shooting quality, and Figure 12 b are
The Bone images that Gauss curved thresholding algorithm is obtained, Figure 12 c are the Bone images that the present embodiment medium filtering thresholding algorithm is obtained；
（3）In rib positioning, by body marker template and rib template the progress relevant matches of establishment independent of x-ray chest radiograph figure
The geometry and position distribution of rib as in, the size of template is adjusted according to the information of image itself, the Shandong of algorithm is improved
Rod；（4）Rib is positioned by relevant matches, compared with Hough transformation, the processing time of image is greatly reduced
（About 50 seconds）, realize the quick positioning of rib；（5）The parameter for weighing matching result is constructed, by analyzing different rotary angle
Spend the linear character of the lower parameter to obtain best matching result so that the positioning of rib is more accurate.
Figure 13 shows the composition structure for the x-ray chest radiograph image processing system that another embodiment of the present invention is provided, in order to just
In explanation, the part related to the embodiment of the present invention illustrate only.
The x-ray chest radiograph image processing system can be applied to various image processing terminals, such as pocket computer（Pocket
Personal Computer, PPC）, palm PC, computer, notebook computer, personal digital assistant（Personal
Digital Assistant, PDA）Deng software unit, hardware cell or software and hardware in these terminals can be operate in
The unit being combined, can also be integrated into these terminals or run on the application system of these terminals as independent suspension member
In.
The x-ray chest radiograph image processing system includes location information acquiring unit 131, initial pictures acquiring unit 132, rib
Image acquisition unit 133, image division unit 134 and rib position determination unit 135.Wherein, the concrete function of each unit
It is as follows：
Believe location information acquiring unit 131, the position for obtaining the positional information of body's border and backbone in x-ray chest radiograph
Breath；
Initial pictures acquiring unit 132, for the position of the body's border obtained according to the location information acquiring unit 131
Confidence ceases, and determines the body region in the x-ray chest radiograph, and multiple body marker templates and the body region by being pre-created
Relevant matches are carried out, the image outside correlation highest body marker template is set to zero to obtain initial pictures；
Bone images acquiring unit 133, for extracting rib from the initial pictures by medium filtering thresholding algorithm
Image；
The Bone images are divided into left and right two by image division unit 134 for the positional information according to the backbone
Individual part；
Rib position determination unit 135, for multiple left and right rib templates by being pre-created respectively with it is described left and right
Two parts carry out relevant matches to obtain dependency graph picture, and the dependency graph picture is divided, and obtain x-ray chest radiograph
The positional information of middle left and right rib.
Further, the relevant matches calculation formula is：
Wherein, f（X, y) represent original image, w（X, y) matching template is represented, F (u, v) represents f（X, y) Fourier become
Change, H (u, v) represents w（X, y) Fourier transformation, "." correlation operation is represented, " * " represents complex conjugate.
Further, the Bone images acquiring unit 133 includes：
Smoothed image acquisition module 1331, obtains smooth for the initial pictures to be carried out with minor radius median filter process
Image；
Bone images acquisition module 1332, for the initial pictures to be carried out with large radius median filter process, and will be big
Image after median radius filtering process is split as threshold plane to the smoothed image, obtains Bone images；
Binary conversion treatment module 1333, for carrying out binary conversion treatment to the Bone images according to predetermined threshold value.
Further, the rib position determination unit 135 includes：
Correlation image collection module 1351, for by the multiple left and right rib templates being pre-created by scaling and/or
The mode of rotation carries out relevant matches with described two parts in left and right respectively, obtains dependency graph picture；
First position determining module 1352, for being door with N times of maximum related value obtained in phase relation matching process
Limit is divided to the dependency graph picture, obtains one or more rib matched positions, and the N is more than zero but less than 1
Constant；
Second place determining module 1353, for described N times be thresholding to one or more of rib matched positions
Divided with the matched position of each rib after being separated；
Wherein, the optimal rotation angle of left and right rib template is obtained by below equation：
Wherein left rib K span is the constant of 0.8≤K≤1.2, and L span is 0.02≤L≤0.03
Constant, K=1, L=0.025 preferably；Right rib K span is the constant of 0.8≤K≤1.2, and L span is 0.8
The constant of≤L≤1.2.
Further, the system also includes：
Fitting unit 136, the center line for obtaining adjacent rib template matches position, and according to the center line, by most
Small square law fits the conic section as rib region line of demarcation.
It is apparent to those skilled in the art that, for convenience and simplicity of description, only with above-mentioned each function
Unit, the division progress of module are for example, in practical application, as needed can distribute above-mentioned functions by different work(
Can unit, module complete, i.e., the internal structure of described system is divided into different functional unit or module, to complete above description
All or part of function.Each functional unit or module in embodiment can be integrated in a processing unit, can also
That unit is individually physically present, can also two or more units it is integrated in a unit, above-mentioned integrated list
Member or module can both be realized in the form of hardware, it would however also be possible to employ the form of SFU software functional unit is realized.In addition, each function
Unit, the specific name of module are also only to facilitate mutually differentiation, is not limited to the protection domain of the application.Above-mentioned system
Unit, the specific work process of module, may be referred to the corresponding process of preceding method embodiment, will not be repeated here in system.
In summary, the beneficial effect that the embodiment of the present invention exists compared with prior art is：（1）Image after will be smooth
The positional information of body's border and the positional information of backbone in x-ray chest radiograph are obtained as the input picture of watershed algorithm, can
The over-segmentation phenomenon of watershed algorithm is effectively reduced, while obvious body's border and backbone in x-ray chest radiograph can be obtained
Positional information；（2）Gauss curved thresholding algorithm is replaced by medium filtering thresholding algorithm, when picture quality is preferable, rib point
Effect is cut close to Gauss curved thresholding algorithm, when picture quality is poor, rib part still can be obtained as far as possible, is improved
The universality of algorithm, in figure 12 it can be seen that compared with Gauss curved thresholding algorithm, the medium filtering threshold value of the present embodiment
Algorithm is had a clear superiority when handling the x-ray chest radiograph image of shooting quality difference, and Figure 12 c are preserved more than Figure 12 b Bone images
Completely, while inhibiting the interference of its hetero-organization of the body interior such as backbone, wherein Figure 12 a are the poor x-ray chest radiographs of shooting quality
Image, Figure 12 b are the Bone images that Gauss curved thresholding algorithm is obtained, and Figure 12 c are that the present embodiment medium filtering thresholding algorithm is obtained
The Bone images taken；（3）In rib positioning, relevant matches are carried out by the body marker template and rib template of establishment and disobeyed
Rely the geometry and position distribution of the rib in x-ray chest radiograph image, the size of template is adjusted according to the information of image itself, is carried
The high robustness of algorithm；（4）Rib is positioned by relevant matches, compared with Hough transformation, figure is greatly reduced
The processing time of picture（About 50 seconds）, realize the quick positioning of rib；（5）The parameter for weighing matching result is constructed, by dividing
Analyse the linear character of the parameter under different rotary angle to obtain best matching result so that the positioning of rib is more accurate.This hair
Bright embodiment has stronger usability and practicality.
Those of ordinary skill in the art are further appreciated that all or part of step realized in above-described embodiment method is can
To instruct the hardware of correlation to complete by program, described program can be stored in a computer read/write memory medium
In, described storage medium, including ROM/RAM, disk, CD etc..
Above content is to combine specific preferred embodiment further description made for the present invention, it is impossible to assert
The specific implementation of the present invention is confined to these explanations.For general technical staff of the technical field of the invention,
Some equivalent substitutes or obvious modification are made on the premise of not departing from present inventive concept, and performance or purposes are identical, all should
It is considered as belonging to the scope of patent protection that the present invention is determined by the claims submitted.
Claims (11)
1. a kind of x-ray chest radiograph image processing method, it is characterised in that methods described includes：
Obtain the positional information and the positional information of backbone of body's border in x-ray chest radiograph；
According to the positional information of the body's border, the body region in the x-ray chest radiograph is determined, and it is many by what is be pre-created
Individual body marker template and the body region carry out relevant matches, by the image outside correlation highest body marker template be set to zero with
Obtain initial pictures；
Bone images are extracted from the initial pictures by medium filtering thresholding algorithm；
The Bone images are divided into by two parts in left and right according to the positional information of the backbone；
Multiple left and right rib templates for being pre-created by way of scaling and/or rotation respectively with described or so two portions
Divide and carry out relevant matches to obtain dependency graph picture, and the dependency graph picture is divided, obtain left and right in x-ray chest radiograph
The positional information of rib.
2. the method as described in claim 1, it is characterised in that the relevant matches calculation formula is：
<mrow>
<mi>f</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
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<mi>w</mi>
<mo>(</mo>
<mrow>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
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<mi>u</mi>
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<mi>H</mi>
<mo>*</mo>
<mo>(</mo>
<mrow>
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<mi>v</mi>
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</mrow>
Wherein, f (x, y) represents original image, and w (x, y) represents matching template, and F (u, v) represents f (x, y) Fourier transformation, H
(u, v) represents w (x, y) Fourier transformation, "." correlation operation symbol is represented, " * " represents complex conjugate operation symbol.
3. the method as described in claim 1, it is characterised in that it is described by medium filtering thresholding algorithm from the initial pictures
Middle extraction Bone images include：
Minor radius median filter process is carried out to the initial pictures and obtains smoothed image；
Large radius median filter process is carried out to the initial pictures, and regard the image after large radius median filter process as threshold
Value plane is split to the smoothed image, obtains Bone images；
Binary conversion treatment is carried out to the Bone images according to predetermined threshold value.
4. the method as described in claim 1, it is characterised in that multiple left and right rib templates by being pre-created pass through
Scaling and/or the mode of rotation carry out relevant matches to obtain dependency graph picture with described two parts in left and right respectively, and right
The dependency graph picture is divided, and is obtained the positional information of left and right rib in x-ray chest radiograph and is included：
By the multiple left and right rib templates being pre-created scale and/or rotation by way of respectively with it is described left and right two parts
Relevant matches are carried out, dependency graph picture is obtained；
The dependency graph picture is divided for thresholding with N times of maximum related value obtained during relevant matches, obtained
One or more rib matched positions are obtained, the N is the constant more than zero but less than 1；
It is that thresholding is divided with each rib after being separated to one or more of rib matched positions with described N times
The matched position of bone.
5. method as claimed in claim 4, it is characterised in that methods described also includes：
The optimal rotation angle of left and right rib template is obtained by below equation：
<mrow>
<mi>Z</mi>
<mo>=</mo>
<msqrt>
<mrow>
<mi>K</mi>
<mo>&CenterDot;</mo>
<msup>
<mi>X</mi>
<mn>2</mn>
</msup>
<mo>+</mo>
<mi>L</mi>
<mo>&CenterDot;</mo>
<msup>
<mi>Y</mi>
<mn>2</mn>
</msup>
</mrow>
</msqrt>
</mrow>
Wherein, the rib POS INT coordinate that X, Y obtain for matching, K, L are weights, wherein left rib K span is 0.8
The constant of≤K≤1.2, L span is the constant of 0.02≤L≤0.03；Right rib K span be 0.8≤K≤
1.2 constant, L span is the constant of 0.8≤L≤1.2.
6. the method as described in any one of claim 1 to 5, it is characterised in that methods described also includes：
The center line of adjacent rib template matches position is obtained, and according to the center line, goes out to be used as rib by least square fitting
The conic section of bone area limit line.
7. a kind of x-ray chest radiograph image processing system, it is characterised in that the system includes：
Location information acquiring unit, for obtaining the positional information of body's border and the positional information of backbone in x-ray chest radiograph；
Initial pictures acquiring unit, for the positional information of the body's border obtained according to the location information acquiring unit, really
Body region in the fixed x-ray chest radiograph, and it is related to body region progress by the multiple body marker templates being pre-created
Property matching, the image outside correlation highest body marker template is set to zero to obtain initial pictures；
Bone images acquiring unit, for extracting Bone images from the initial pictures by medium filtering thresholding algorithm；
The Bone images are divided into two parts in left and right by image division unit for the positional information according to the backbone；
Rib position determination unit, scaling and/or the side rotated are passed through for multiple left and right rib templates by being pre-created
Formula carries out relevant matches to obtain dependency graph picture with described two parts in left and right respectively, and the dependency graph picture is carried out
Divide, obtain the positional information of left and right rib in x-ray chest radiograph.
8. system as claimed in claim 7, it is characterised in that the relevant matches calculation formula is：
<mrow>
<mi>f</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
<mo>.</mo>
<mi>w</mi>
<mo>(</mo>
<mrow>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
</mrow>
<mo>)</mo>
<mo>&DoubleLeftRightArrow;</mo>
<mi>F</mi>
<mrow>
<mo>(</mo>
<mi>u</mi>
<mo>,</mo>
<mi>v</mi>
<mo>)</mo>
</mrow>
<mi>H</mi>
<mo>*</mo>
<mo>(</mo>
<mrow>
<mi>u</mi>
<mo>,</mo>
<mi>v</mi>
</mrow>
<mo>)</mo>
</mrow>
Wherein, f (x, y) represents original image, and w (x, y) represents matching template, and F (u, v) represents f (x, y) Fourier transformation, H
(u, v) represents w (x, y) Fourier transformation, "." correlation operation symbol is represented, " * " represents complex conjugate operation symbol.
9. system as claimed in claim 7, it is characterised in that the Bone images acquiring unit includes：
Smoothed image acquisition module, smoothed image is obtained for carrying out minor radius median filter process to the initial pictures；
Bone images acquisition module, for carrying out large radius median filter process to the initial pictures, and by large radius intermediate value
Image after filtering process is split as threshold plane to the smoothed image, obtains Bone images；
Binary conversion treatment module, for carrying out binary conversion treatment to the Bone images according to predetermined threshold value.
10. system as claimed in claim 7, it is characterised in that the rib position determination unit includes：
Correlation image collection module, for the multiple left and right rib templates being pre-created to be passed through into scaling and/or the side rotated
Formula carries out relevant matches with described two parts in left and right respectively, obtains dependency graph picture；
First position determining module, for being thresholding to described with N times of maximum related value obtained during relevant matches
Dependency graph picture is divided, and obtains one or more rib matched positions, and the N is the constant more than zero but less than 1；
Second place determining module, for being that thresholding is divided to one or more of rib matched positions with described N times
With the matched position of each rib after being separated；
Wherein, the optimal rotation angle of left and right rib template is obtained by below equation：
<mrow>
<mi>Z</mi>
<mo>=</mo>
<msqrt>
<mrow>
<mi>K</mi>
<mo>&CenterDot;</mo>
<msup>
<mi>X</mi>
<mn>2</mn>
</msup>
<mo>+</mo>
<mi>L</mi>
<mo>&CenterDot;</mo>
<msup>
<mi>Y</mi>
<mn>2</mn>
</msup>
</mrow>
</msqrt>
</mrow>
Wherein left rib K span is the constant of 0.8≤K≤1.2, and L span is the normal of 0.02≤L≤0.03
Number；Right rib K span is the constant of 0.8≤K≤1.2, and L span is the constant of 0.8≤L≤1.2.
11. the system as described in any one of claim 7 to 10, it is characterised in that the system also includes：
Fitting unit, the center line for obtaining adjacent rib template matches position, and according to the center line, pass through least square method
Fit the conic section as rib region line of demarcation.
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| CN106611411B (en) * | 2015-10-19 | 2020-06-26 | 上海联影医疗科技有限公司 | Method for segmenting ribs in medical image and medical image processing device |
| CN105869163B (en) * | 2016-03-26 | 2018-12-11 | 南方医科大学 | Method based on the gradient correlation of bone picture and soft tissue picture detection motion artifacts region in dual energy subtraction |
| WO2018159535A1 (en) * | 2017-02-28 | 2018-09-07 | 株式会社島津製作所 | Image processing method |
| CN109978773A (en) * | 2017-12-27 | 2019-07-05 | 浙江宇视科技有限公司 | Image processing method and device |
| CN109124662B (en) * | 2018-07-13 | 2021-12-03 | 上海皓桦科技股份有限公司 | Rib center line detection device and method |
| CN109840546B (en) * | 2019-01-04 | 2023-02-03 | 南方医科大学南方医院 | Method, system and storage medium for identifying mark and matching information of X-ray image |
| CN111311612A (en) * | 2020-02-17 | 2020-06-19 | 北京推想科技有限公司 | Lung segmentation method, device, medium, and electronic apparatus |
| CN111476777B (en) * | 2020-04-07 | 2023-08-22 | 上海联影智能医疗科技有限公司 | Chest radiography image processing method, system, readable storage medium and apparatus |
| CN113160248B (en) * | 2021-04-22 | 2023-03-14 | 浙江明峰智能医疗科技有限公司 | Image processing method, device and equipment and readable storage medium |
| CN114638828B (en) * | 2022-05-18 | 2022-09-23 | 数聚(山东)医疗科技有限公司 | Radiological image intelligent segmentation method based on computer vision |
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