CN104700419A - Image handling method of X-ray picture of radiology department - Google Patents

Abstract

The invention discloses an image handling method of an X-ray picture of radiology department. The method comprises the steps of acquiring a 3D actual measuring map through an X-ray picture instrument; matching with a pre-stored 3D reference map by the image to obtain all point pairs between the actual measuring map and the reference map, wherein the point pairs are respectively corresponding to each other; calculating the pixel difference of each respectively-corresponding point pair; reconstructing a target image according to the pixel difference; obtaining the parameters value of the target image; outputting the processed data. With the adoption of the method, medical staff can be directly read the specifically-measured value which is different from the normal value through the obtained data, thus lots of diagnosis time and the time of observing the X-ray picture can be saved, and as a result, the working efficiency can be increased, and the accuracy of the diagnosis result can be increased.

Description

The image processing method of a kind of dept. of radiology X-ray

Technical field

The invention belongs to image processing field, be specifically related to the image processing method of a kind of dept. of radiology X-ray.

Background technology

X mating plate is that a pictures is become gray-scale map by Gray filter; Invert filter is that the visual attribute of object is all overturn, and comprises color, saturation degree and brightness value; Xray filter allows object reflect its profile and these profiles are highlighted, namely so-called " X " mating plate.

Dept. of radiology is the one in numerous section office.Dept. of radiology is important auxiliary examination section office of hospital, in modern hospital is built, dept. of radiology is that a collection checks, diagnoses, treats one section office, clinical departments numerous disease all must be reached by dept. of radiology's equipment inspection clarifies a diagnosis and auxiliary diagnosis, and the consultation of doctors comprises: bone tumour and Tumor-like Lesion, bone and soft-tissue trauma, bone myokinesis damages, bone congenital development illness, the bone disorder that heredity and metabolism cause, the difficult and complicated illness of other skeletal musculatures.Consultation of doctors personnel component: by there is the associate chief physician that is engaged in musculoskeletal system iconography clinical diagnosis experience for many years or chief physician carries out hold a consultation (introduce in detail and see expert's brief introduction).Consultation of doctors mode: carry the imaging examination (comprising X plain film, CT sheet, MRI, B ultrasonic, isotopic examination etc.) of all information by sufferers themselves or family members and concise and to the point clinical examination data is held a consultation to dept. of radiology's Consultation Center.

The responsibility of the doctor of dept. of radiology mainly carry out ordinary x-ray film, Trauma Tomography (CT), with the medical image work such as magnetic resonance imaging (MRI), for clinician provides diagnosis support, analysis contrast is carried out to image data, the suggestion drawing diagnostic comments or check further.

At present, the dept. of radiology of major part hospital still adopts the mode of eye-observation to X-ray, the film making instrument of some advanced persons also can print concrete parameter, but these parameters directly print based on the mating plate taken, corresponding process is not done to image, therefore, even if print, also need a large amount of consultation of doctors supervisors, can not find out the deviation with normal value intuitively, diagnosis efficiency is low.

Application number is 201310269818.9, and the applying date is that on 06 28th, 2013 invention disclosed patents provide a kind of x-ray chest radiograph image processing method and system, and the method comprises: obtain the positional information of body's border and the positional information of backbone in x-ray chest radiograph; According to the positional information of described body's border, determine the body region in x-ray chest radiograph, and carry out relevant matches by multiple body marker template of being pre-created and described body region, the image outside body marker template the highest for correlativity is set to zero to obtain initial pictures; From described initial pictures, Bone images is extracted by medium filtering thresholding algorithm; Described Bone images is divided into two parts in left and right by the positional information according to described backbone; Carry out relevant matches to obtain correlativity image with two, described left and right part respectively by the multiple left and right rib template be pre-created, and described correlativity image is divided, obtain the positional information of left and right rib in x-ray chest radiograph.Can be positioned the rib in x-ray chest radiograph fast and accurately by the present invention.

Above-mentioned patent solves the problem of quick position, but does not do further process to the mating plate image taken, and can not draw final conclusion fast, and for the post-processed taking mating plate, the method also fails to provide solution effectively and rapidly.

Summary of the invention

Technical matters to be solved by this invention is: the image processing method providing a kind of dept. of radiology X-ray, solves that dept. of radiology in prior art is low to X-ray analyzing and processing efficiency, slow problem of holding a consultation.

The present invention is for solving the problems of the technologies described above by the following technical solutions:

An image processing method for dept. of radiology's X-ray, first gathers three-dimensional measured drawing by X-ray instrument, and carries out images match with the three-dimensional reference diagram prestored, and obtains all one-to-one points pair between measured drawing and reference diagram; Then, calculate the pixel value difference that every a pair one-to-one point is right, rebuild target image according to pixel value difference; Finally, obtain the parameter value of target image, the data after process export; Wherein, carry out images match, the detailed process obtaining all one-to-one points between measured drawing and reference diagram right is as follows:

With reference to the pixel point set of figure with measured drawing, be defined as set A and B respectively, choose arbitrarily two groups of points pair, wherein, often to select for a pair all comprising selecting and point in a measuring image vegetarian refreshments collection B in a reference picture vegetarian refreshments collection A, and the coordinate of every a pair centering two points is different, each is put two right points and forms a zeroaxial vector, two vectors form plane, then the angle between two vectors is:

Wherein, a _ifor i-th element in set A, a _jfor the element of jth in set A, b _pfor p element in set B, b _qfor q element in set B, a _i≠ a _j, b _p≠ b _q;

The normal vector of the zeroaxial normal of plane that two vectors are formed is:

direction vector is: $\stackrel{\→}{\mathrm{ne}}=\frac{\stackrel{\→}{n}}{\left|\right|\stackrel{\→}{n}\left|\right|}=(l,m,n)$

Wherein l, m, n are respectively with X, Y, the direction cosine of Z axis, judge wherein whether one group of corresponding point are to being one-to-one point pair; If one-to-one point pair, record this group of one-to-one point pair; Otherwise continue to judge;

All one-to-one points pair between record reference diagram and measured drawing.

The pixel value difference that every a pair one-to-one point of described calculating is right, the detailed process rebuilding target image according to pixel value difference is as follows:

First, obtain the pixel-parameters of each group one-to-one point centering measuring image vegetarian refreshments, and carry out correspondingly asking difference, using the pixel-parameters of all differences as target pixel points, according to the pixel-parameters establishing target image of all target pixel points with the pixel-parameters of corresponding reference picture vegetarian refreshments.

Described pixel-parameters comprises brightness value, gray-scale value, chromatic value, the D coordinates value of pixel.

Described judgement wherein one group of corresponding point to be whether one-to-one point to adopting with the following method:

By the vector of two element structures in set A with direction vector be zeroaxial normal is turning axle, rotates θ angle around turning axle, and make this vector consistent with the direction vector that two elements in set B build, then this rotational transform three-dimensional matrice is expressed as:

$P(\mathrm{\θ},0)=\left[\begin{array}{ccc}{l}^2(1-\cos \mathrm{\θ})+\cos \mathrm{\θ}& \mathrm{ml}(1-\cos \mathrm{\θ})+n\sin \mathrm{\θ}& \mathrm{nl}(1-\cos \mathrm{\θ})-m\sin \mathrm{\θ}\\ \mathrm{ml}(1-\cos \mathrm{\θ})-n\sin \mathrm{\θ}& m^2(1-\cos \mathrm{\θ})+\cos \mathrm{\θ}& \mathrm{nm}(1-\cos \mathrm{\θ})+l\sin \mathrm{\θ}\\ \mathrm{nl}(1-\cos \mathrm{\θ})+m\sin \mathrm{\θ}& \mathrm{nm}(1-\cos \mathrm{\θ})-l\sin \mathrm{\θ}& n^2(1-\cos \mathrm{\θ})+\cos \mathrm{\θ}\end{array}\right]$

Judge whether this rotational transform three-dimensional matrice P (θ, 0) is optimum similitude transformation matrix; If P (θ, 0) is optimum similar matrix, then defining this optimum similar matrix is P _g(θ, 0), these group of corresponding point is to being one-to-one point pair simultaneously.

The parameter value of described target image, the data after process comprise the print data exporting printing device to, export the display data of display device to, and export the store backup data of memory device to.

One-to-one point between described actual measurement 3-D view and reference 3-D view calculates utilizing least-squares algorithm.

Compared with prior art, the present invention has following beneficial effect:

1, by calculating the right pixel value difference of every a pair one-to-one point, target image is rebuild according to pixel value difference; Finally, obtain the parameter value of target image, the data after process export, make medical worker can find out the concrete value with normal value deviation intuitively, save a large amount of consultation of doctors time and observed the mating plate time, having improve work efficiency, and having added the accuracy rate of consultation of doctors conclusion.

2, analyze reconstruct target image for the parameter that each pixel is different, make the target image of reconstruct more clear, accurate, validity is higher.

3, least-squares algorithm is adopted to carry out exact matching algorithm by three-dimensional measuring image and three-dimensional reference picture, calculate position and the attitudes vibration of image in X-ray, because the precision calculated can reach sub-pixel, therefore the method positioning precision of the present invention's employing is high.

Accompanying drawing explanation

Fig. 1 is image space swing offset figure of the present invention.

Embodiment

Below in conjunction with accompanying drawing, structure of the present invention and the course of work are described further.

An image processing method for dept. of radiology's X-ray, first gathers three-dimensional measured drawing by X-ray instrument, and carries out images match with the three-dimensional reference diagram prestored, and obtains all one-to-one points pair between measured drawing and reference diagram; Then, calculate the pixel value difference that every a pair one-to-one point is right, rebuild target image according to pixel value difference; Finally, obtain the parameter value of target image, the data after process export; Wherein, carry out images match, the detailed process obtaining all one-to-one points between measured drawing and reference diagram right is as follows:

With reference to the pixel point set of figure with measured drawing, be defined as set A and B respectively, choose arbitrarily two groups of points pair, wherein, often to select for a pair all comprising selecting and point in a measuring image vegetarian refreshments collection B in a reference picture vegetarian refreshments collection A, and the coordinate of every a pair centering two points is different, each is put two right points and forms a zeroaxial vector, two vectors form plane, then the angle between two vectors is:

Wherein, a _ifor i-th element in set A, a _jfor the element of jth in set A, b _pfor p element in set B, b _qfor q element in set B, a _i≠ a _j, b _p≠ b _q;

The normal vector of the zeroaxial normal of plane that two vectors are formed is:

direction vector is: $\stackrel{\→}{\mathrm{ne}}=\frac{\stackrel{\→}{n}}{\left|\right|\stackrel{\→}{n}\left|\right|}=(l,m,n)$

Wherein l, m, n are respectively with X, Y, the direction cosine of Z axis, judge wherein whether one group of corresponding point are to being one-to-one point pair; If one-to-one point pair, record this group of one-to-one point pair; Otherwise continue to judge;

All one-to-one points pair between record reference diagram and measured drawing.

Described image matching algorithm mainly comprises the steps:

A () determines the point set to be matched between measured drawing and reference diagram;

B () determines to have the real number matrix of maximum matching double points number and one group of one-to-one point pair between measuring image and reference picture;

(c) obtain between measuring image and reference picture one group of one-to-one point to the real number matrix basis with maximum matching double points number on, determine one-to-one points pair all in measured drawing and reference diagram;

D () is obtaining all one-to-one points on basis, adopt least-squares algorithm to calculate optimum real number transformation matrix.

Exact image matching algorithm for convenience of description, first defines optimum real number transformation matrix: the pixel of stereo-picture is expanded into three-dimensional point wherein, for the coordinate of X-axis corresponding on three dimensions, Y-axis and Z axis, the point set of hypothetical reference figure and measured drawing is respectively A={a ₁, a ₂..., a _mand B={b ₁, b ₂..., b _n, next defines vector wherein a _i, a _jwith b _p, b _qbe respectively the point that reference diagram point set and measured drawing point are concentrated, and a _i≠ a _j, b _p≠ b _q, and with be two groups of one-to-one points pair, then vectors to vector angle be:

Vector the normal vector of the zeroaxial normal of the plane formed is:

Direction vector after normal vector is unitization:

$\stackrel{\→}{\mathrm{ne}}=\frac{\stackrel{\→}{n}}{\left|\right|\stackrel{\→}{n}\left|\right|}=(l,m,n,0),$

Wherein l, m, n are respectively with X, Y, the direction cosine of Z axis, so vector with direction vector be zeroaxial straight line is turning axle, after turning axle rotates θ angle, with vector direction is consistent, as shown in Figure 1, the Space Rotating of 3-D view can be expressed as and comprise around the rotary motion (anglec of rotation is θ) of a certain screw axis with along the translation motion (displacement is S) in helical axis directions, image is h to the distance of turning axle, then this rotational transform three-dimensional matrice is expressed as:

$P(\mathrm{\θ},0)=\left[\begin{array}{ccc}{l}^2(1-\cos \mathrm{\θ})+\cos \mathrm{\θ}& \mathrm{ml}(1-\cos \mathrm{\θ})+n\sin \mathrm{\θ}& \mathrm{nl}(1-\cos \mathrm{\θ})-m\sin \mathrm{\θ}\\ \mathrm{ml}(1-\cos \mathrm{\θ})-n\sin \mathrm{\θ}& m^2(1-\cos \mathrm{\θ})+\cos \mathrm{\θ}& \mathrm{nm}(1-\cos \mathrm{\θ})+l\sin \mathrm{\θ}\\ \mathrm{nl}(1-\cos \mathrm{\θ})+m\sin \mathrm{\θ}& \mathrm{nm}(1-\cos \mathrm{\θ})-l\sin \mathrm{\θ}& n^2(1-\cos \mathrm{\θ})+\cos \mathrm{\θ}\end{array}\right]$

Judge whether this rotational transform three-dimensional matrice P (θ, 0) is optimum similitude transformation matrix; If P (θ, 0) is optimum similar matrix, then defining this optimum similar matrix is P _g(θ, 0), these group of corresponding point is to being one-to-one point pair simultaneously.

Suppose two point set A={a ₁, a ₂..., a _mand B={b ₁, b ₂..., b _nbetween there is k one-to-one point, namely $a_i\↔b_i,i=\mathrm{1,2},...,k,$ Then for any one group of corresponding point pair $a_i\↔b_i,i=\mathrm{1,2},...,k,$ There is set of vectors with similarity transformation between corresponding vector is P (α, 0), therefore, if when being one group of corresponding point pair, k-1 other points must being determined in point set A and B, in order to form corresponding vector pair, and be P (θ, 0) by any pair determined similarity transformation of vector.Otherwise, if counting of determining is less than k, then should for mutually not corresponding point is right, and can know that actual one-to-one point logarithm should be less than or equal to k-1, by that analogy, the number that the maximum one-to-one point of point set is right can be found.Definition real number similitude transformation matrix is now P _op(θ, 0), utilizes this similitude transformation matrix whether can judge one group of given corresponding point to as putting the one group of one-to-one point pair concentrated.

The pixel value difference that every a pair one-to-one point of described calculating is right, the detailed process rebuilding target image according to pixel value difference is as follows:

First, obtain the pixel-parameters of each group one-to-one point centering measuring image vegetarian refreshments, and carry out correspondingly asking difference, using the pixel-parameters of all differences as target pixel points, according to the pixel-parameters establishing target image of all target pixel points with the pixel-parameters of corresponding reference picture vegetarian refreshments.

Described pixel-parameters comprises brightness value, gray-scale value, chromatic value, the D coordinates value of pixel.

The parameter value of described target image, the data after process comprise the print data exporting printing device to, export the display data of display device to, and export the store backup data of memory device to.

One-to-one point between described actual measurement 3-D view and reference 3-D view calculates utilizing least-squares algorithm.

Described least-squares algorithm principle is: two the one_to_one corresponding point set A={a supposing given space ₁, a ₂..., a _nand B={b ₁, b ₂..., b _n, need to find real number transformation matrix P (R, t), make to obtain minimum value using the quadratic sum of error as objective function.When objective function gets minimum value, can think that point set A with B is issued to farthest similar at this real number transformation matrix.Wherein, objective function is:

$e^2(R,t)=\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\left|\right|b_i-P(R,t)a_i\left|\right|}^2$

For one group of corresponding point that two one-to-one points are concentrated can obtain according to similarity transformation relation:

b _i＝P(R,t)a _i，

Definition error vector is e _i, what calculate two one_to_one corresponding point sets successively often organizes the right error vector e of corresponding point ₁, e ₂..., e _n, obtain according to objective function:

$\begin{array}{c}{e}^2=\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\left|\right|e_i\left|\right|}^2=\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{e}_i^T{e}_i=\frac{1}{n}(e_1^T{e}_1+e_2^T{e}_2+...+e_n^T{e}_n)\\ =\frac{1}{n}(\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{e}_{\mathrm{xi}}^2+\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{e}_{\mathrm{yi}}^2+\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{e}_{\mathrm{zi}}^2+\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{e}_{\mathrm{wi}}^2)\end{array}$

Make in equation that each all obtains minimum value, make e ²obtain minimum value, determine optimum real number matrix, the real number matrix that can be obtained by exact image matching algorithm calculates the parameter shift amount of measuring image relative to reference picture.

According to all one-to-one points pair that images match obtains, utilize least square method to calculate the value of element in P, obtain final pixel-parameters difference.

Those skilled in the art of the present technique are understandable that, unless otherwise defined, all terms used herein (comprising technical term and scientific terminology) have the meaning identical with the general understanding of the those of ordinary skill in field belonging to the present invention.Should also be understood that those terms defined in such as general dictionary should be understood to have the meaning consistent with the meaning in the context of prior art, unless and define as here, can not explain by idealized or too formal implication.

The above is only some embodiments of the present invention; it should be pointed out that for those skilled in the art, under the premise without departing from the principles of the invention; can also make some improvements and modifications, these improvements and modifications also should be considered as protection scope of the present invention.

Claims (6)

1. an image processing method for dept. of radiology's X-ray, is characterized in that: first gather three-dimensional measured drawing by X-ray instrument, and carries out images match with the three-dimensional reference diagram prestored, and obtains all one-to-one points pair between measured drawing and reference diagram; Then, calculate the pixel value difference that every a pair one-to-one point is right, rebuild target image according to pixel value difference; Finally, obtain the parameter value of target image, the data after process export; Wherein, carry out images match, the detailed process obtaining all one-to-one points between measured drawing and reference diagram right is as follows:

With reference to the pixel point set of figure with measured drawing, be defined as set A and B respectively, choose arbitrarily two groups of points pair, wherein, often to select for a pair all comprising selecting and point in a measuring image vegetarian refreshments collection B in a reference picture vegetarian refreshments collection A, and the coordinate of every a pair centering two points is different, each is put two right points and forms a zeroaxial vector, two vectors form plane, then the angle between two vectors is:

$\mathrm{\θ}={\cos }^{-1}\frac{\stackrel{\→}{a_i{a}_j}\·\stackrel{\→}{b_p{b}_q}}{\left|\right|\stackrel{\→}{a_i{a}_j}\left|\right|\·\left|\right|\stackrel{\→}{b_p{b}_q}\left|\right|},$

Wherein, a _ifor i-th element in set A, a _jfor the element of jth in set A, b _pfor p element in set B, b _qfor q element in set B, a _i≠ a _j, b _p≠ b _q;

The normal vector of the zeroaxial normal of plane that two vectors are formed is:

$\stackrel{\→}{n}=\stackrel{\→}{a_i}{a}_j\×\stackrel{\→}{b_p{b}_q},$ Direction vector is: $\stackrel{\→}{\mathrm{ne}}=\frac{\stackrel{\→}{n}}{\left|\right|\stackrel{\→}{n}\left|\right|}=(l,m,n)$

Wherein l, m, n are respectively with X, Y, the direction cosine of Z axis, judge wherein whether one group of corresponding point are to being one-to-one point pair; If one-to-one point pair, record this group of one-to-one point pair; Otherwise continue to judge;

All one-to-one points pair between record reference diagram and measured drawing.

2. the image processing method of dept. of radiology according to claim 1 X-ray, is characterized in that: the pixel value difference that every a pair one-to-one point of described calculating is right, and the detailed process rebuilding target image according to pixel value difference is as follows:

First, obtain the pixel-parameters of each group one-to-one point centering measuring image vegetarian refreshments, and carry out correspondingly asking difference, using the pixel-parameters of all differences as target pixel points, according to the pixel-parameters establishing target image of all target pixel points with the pixel-parameters of corresponding reference picture vegetarian refreshments.

3. the image processing method of dept. of radiology according to claim 2 X-ray, is characterized in that: described pixel-parameters comprises brightness value, gray-scale value, chromatic value, the D coordinates value of pixel.

4. the image processing method of dept. of radiology according to claim 1 X-ray, is characterized in that: described judgement wherein one group of corresponding point to be whether one-to-one point to adopting with the following method:

By the vector of two element structures in set A with direction vector be zeroaxial normal is turning axle, rotates θ angle around turning axle, and make this vector consistent with the direction vector that two elements in set B build, then this rotational transform three-dimensional matrice is expressed as:

$P(\mathrm{\θ},0)=\left[\begin{array}{ccc}{l}^2(1-\cos \mathrm{\θ})+\cos \mathrm{\θ}& \mathrm{ml}(1-\cos \mathrm{\θ})+n\sin \mathrm{\θ}& \mathrm{nl}(1-\cos \mathrm{\θ})-m\sin \mathrm{\θ}\\ \mathrm{ml}(1-\cos \mathrm{\θ})-n\sin \mathrm{\θ}& m^2(1-\cos \mathrm{\θ})+\cos \mathrm{\θ}& \mathrm{nm}(1-\cos \mathrm{\θ})+l\sin \mathrm{\θ}\\ \mathrm{nl}(1-\cos \mathrm{\θ})+m\sin \mathrm{\θ}& \mathrm{nm}(1-\cos \mathrm{\θ})-l\sin \mathrm{\θ}& n^2(1-\cos \mathrm{\θ})+\cos \mathrm{\θ}\end{array}\right]$

Judge whether this rotational transform three-dimensional matrice P (θ, 0) is optimum similitude transformation matrix; If P (θ, 0) is optimum similar matrix, then defining this optimum similar matrix is P _g(θ, 0), these group of corresponding point is to being one-to-one point pair simultaneously.

5. the image processing method of dept. of radiology according to claim 1 X-ray, it is characterized in that: the parameter value of described target image, data after process comprise the print data exporting printing device to, export the display data of display device to, and export the store backup data of memory device to.

6. the image processing method of dept. of radiology according to claim 1 X-ray, is characterized in that: the one-to-one point between described actual measurement 3-D view and reference 3-D view calculates utilizing least-squares algorithm.