CN107301622A - The panoramic picture acquisition methods and system of oral cavity CBCT images - Google Patents
The panoramic picture acquisition methods and system of oral cavity CBCT images Download PDFInfo
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Abstract
The present invention relates to a kind of panoramic picture acquisition methods of oral cavity CBCT images and system.The panoramic picture acquisition methods of above-mentioned oral cavity CBCT images include：One, which is selected, in multiple continuous two-dimentional oral cavity CBCT images contains the two-dimentional oral cavity CBCT images of tooth structure image as target two dimensional image；Dental arch curve is recognized on the target two dimensional image, the dental arch curve of each two-dimentional oral cavity CBCT image is determined according to the dental arch curve on the target two dimensional image；Equidistantly sampled on the dental arch curve of each two-dimentional oral cavity CBCT image respectively, obtain multiple sampled points on each two-dimentional oral cavity CBCT images, each multiple sampled point of two-dimentional oral cavity CBCT picture positions identical is defined as one group of sampled point；The corresponding sampling matrix of each group sampled point is obtained, forward projection operation is weighted to each sampling matrix respectively, obtains multiple weighting matrixs；Each weighting matrix is spliced in sequence, the panoramic picture of the oral cavity CBCT images is obtained according to splicing result.
Description
Technical field
The present invention relates to technical field of image processing, more particularly to a kind of panoramic picture acquisition side of oral cavity CBCT images
Method and system.
Background technology
For the cone-beam X-ray ct apparatus (abbreviation oral cavity CBCT) in oral cavity, collected by circumference
Data for projection under all angles of the region such as human oral cavity carries out image reconstruction, can obtain a series of axial face images, referred to as
CBCT images, are enumerated into 3-D view along the direction perpendicular to paper.Using CBCT images, image processing method can be passed through
Method obtains panorama sketch (also referred to as surface fault figure), and examining for odontopathy is carried out by CBCT images and panoramic picture beneficial to doctor
It is disconnected.CBCT generation panorama sketch general principle be：Curve C is delineated along teeth arrangement direction on a certain layer CBCT images, is counted
Calculate the normal direction of each point on curve, the point centered on curve point, the pixel value along in normal direction or so certain thickness
Added up, obtain an accumulated value, all curve points and corresponding normal can obtain an accumulated value, according to curve
Putting in order for point is arranged in a line to corresponding accumulated value, and other each layer CBCT images do same according to the curve C delineated
Processing, each layer can all obtain one-dimensional row data, many one-dimensional row data are sorted line by line according to the order of each layers of CBCT,
Just obtain the oral cavity panorama sketch of two dimension.
In the panoramic picture acquisition scheme of traditional oral cavity CBCT images, there is one on related panorama sketch is calculated of technology
During the value of point, the gray value away from curve and the gray value close to curve are easily caused two teeth on normal to curve and interlocked
In the case of, picture structure blur margin is clear；Also technology carry out panorama point value calculate when, using on normal with it is corresponding song
The average value of the close all multivalues of the pixel value of line point is as panorama point value, it is necessary to which threshold value judges which pixel value belongs to same
Class, when the difference of threshold value setting can influence final result, especially picture noise level increase, necessarily affects final meter
Calculate result；On the other hand, the panoramic picture obtained using the panoramic picture acquisition scheme of above-mentioned traditional oral cavity CBCT images is deposited
Human eye vision custom is not being met, the defect that the human eye of observer is not regarded as point source to consider is easily caused acquired
Panoramic picture do not meet human eye vision observation characteristic.
The content of the invention
Based on this, it is necessary to be easily caused acquired panoramic picture for traditional scheme and do not meet human eye vision observation spy
There is provided a kind of panoramic picture acquisition methods of oral cavity CBCT images and system for the technical problem of property.
A kind of panoramic picture acquisition methods of oral cavity CBCT images, comprise the following steps：
A two-dimentional oral cavity CBCT containing tooth structure image is selected in multiple continuous two-dimentional oral cavity CBCT images
Image is used as target two dimensional image；
Dental arch curve is recognized on the target two dimensional image, is determined according to the dental arch curve on the target two dimensional image
The dental arch curve of each two-dimentional oral cavity CBCT image；
Equidistantly sampled on the dental arch curve of each two-dimentional oral cavity CBCT image respectively, obtain each two-dimentional oral cavity CBCT
Each multiple sampled point of two-dimentional oral cavity CBCT picture positions identical is defined as one group of sampling by multiple sampled points on image
Point；
The corresponding sampling matrix of each group sampled point is obtained, forward projection operation is weighted to each sampling matrix respectively,
Obtain multiple weighting matrixs；
Each weighting matrix is spliced in sequence, the panorama of the oral cavity CBCT images is obtained according to splicing result
Image.
A kind of panoramic picture of oral cavity CBCT images obtains system, including：
Selecting module, contains tooth structure image for selecting one in multiple continuous two-dimentional oral cavity CBCT images
Two-dimentional oral cavity CBCT images are used as target two dimensional image；
Identification module, for recognizing dental arch curve on the target two dimensional image, according on the target two dimensional image
Dental arch curve determine the dental arch curve of each two-dimentional oral cavity CBCT image；
Sampling module, for equidistantly being sampled on the dental arch curve of each two-dimentional oral cavity CBCT image respectively, is obtained
Multiple sampled points on each two-dimentional oral cavity CBCT images, each multiple sampled point of two-dimentional oral cavity CBCT picture positions identical are true
It is set to one group of sampled point；
Acquisition module, for obtaining the corresponding sampling matrix of each group sampled point, is weighted to each sampling matrix respectively
Forward projection is operated, and obtains multiple weighting matrixs；
Concatenation module, for each weighting matrix to be spliced in sequence, the oral cavity is obtained according to splicing result
The panoramic picture of CBCT images.
The panoramic picture acquisition methods and system of above-mentioned oral cavity CBCT images, by multiple continuous two-dimentional oral cavity CBCT
Equidistantly sampled on the dental arch curve of image, obtain multiple sampled points on each two-dimentional oral cavity CBCT images, by each two dimension
Identical multiple sampled points in oral cavity CBCT picture positions are defined as one group of sampled point, and then obtain the corresponding sampling of each group sampled point
Matrix, to obtain corresponding weighting matrix, then each weighting matrix is spliced in sequence, and institute is obtained according to splicing result
The panoramic picture of oral cavity CBCT images is stated, resulting panoramic picture is covered entrained by each above-mentioned two-dimentional oral cavity CBCT image
Feature, with higher accuracy, more conform to the Visual Observations Observations characteristic of human eye.
A kind of computer-readable recording medium, is stored thereon with computer program, and the computer program is executed by processor
The panoramic picture acquisition methods of Shi Shixian CBCT images in oral cavity as described above.
The computer program stored on above computer readable storage medium storing program for executing, can realize as above institute when being executed by processor
The panoramic picture acquisition methods for the oral cavity CBCT images stated, can improve the acquisition effect of corresponding panoramic picture, make acquired
Panoramic picture more conforms to the Visual Observations Observations characteristic of human eye.
A kind of computer equipment, including memory, processor and storage can be run on a memory and on a processor
Computer program, realizes the panoramic picture acquisition side of CBCT images in oral cavity as described above during the computing device described program
Method.
CBCT images in oral cavity as described above can be realized in above computer equipment, during computing device described program
Panoramic picture acquisition methods, effectively increase the acquisition effect of corresponding panoramic picture, more conform to acquired panoramic picture
The Visual Observations Observations characteristic of human eye.
Brief description of the drawings
Fig. 1 is the panoramic picture acquisition methods flow chart of the oral cavity CBCT images of one embodiment；
Fig. 2 is part sampled point schematic diagram on the two-dimentional oral cavity CBCT images arcus dentalis superior curve of one embodiment；
Fig. 3 is the transmitting reference point and pixel-matrix schematic diagram of one embodiment；
Fig. 4 is one layer of CBCT two dimensional image schematic diagram of one embodiment；
Fig. 5 is the seed point schematic diagram of one embodiment；
Fig. 6 is the dental arch curve schematic diagram of one embodiment；
Fig. 7 is the transmitting reference point and pixel-matrix schematic diagram of one embodiment；
Fig. 8 is the panoramic picture schematic diagram of one embodiment；
Fig. 9 obtains system structure diagram for the panoramic picture of the oral cavity CBCT images of one embodiment；
Figure 10 is the computer equipment structural representation of one embodiment.
Embodiment
Panoramic picture acquisition methods to oral cavity CBCT images of the invention and the specific implementation of system below in conjunction with the accompanying drawings
Mode is described in detail.
With reference to Fig. 1, Fig. 1 show the panoramic picture acquisition methods flow chart of the oral cavity CBCT images of one embodiment, bag
Include following steps：
S10, selects a two-dimentional oral cavity containing tooth structure image in multiple continuous two-dimentional oral cavity CBCT images
CBCT images are used as target two dimensional image；
Above-mentioned two-dimentional oral cavity CBCT images are multiple continuous X-Y schemes of the oral cavity structure for panoramic picture to be obtained
The plane picture of the two-dimentional oral cavity CBCT images correspondence oral cavity structure one end of piece, i.e., first, second two-dimentional oral cavity CBCT image
A correspondence plane picture ... ... adjacent with the plane picture of above-mentioned oral cavity structure one end, last two-dimentional oral cavity CBCT
Image correspondence and the plane picture of the above-mentioned oral cavity structure other end.Pixel included by each above-mentioned two-dimentional oral cavity CBCT image
Number feature (including number of lines of pixels and pixel columns) is identical, thus according to pixel correspondence in each two-dimentional oral cavity CBCT image
Pixel value generation image array model it is identical, be M*M matrixes, i.e. M rows M column matrix.Above-mentioned multiple continuous two-dimentional mouths
Several two-dimentional oral cavity CBCT images in chamber CBCT images contain the image of the tooth structure in oral cavity structure, by it is above-mentioned containing
The two-dimentional oral cavity CBCT images of one of tooth structure image are chosen to be target two dimensional image, to carry out corresponding dental arch curve really
It is fixed.
S20, dental arch curve is recognized on the target two dimensional image, according to the dental arch curve on the target two dimensional image
Determine the dental arch curve of each two-dimentional oral cavity CBCT image；
Specifically, above-mentioned steps can obtain dental arch curve therein by computer in target two dimensional image, can also
Denture on the CBCT images of two-dimentional oral cavity is recognized by relevant speciality personage, corresponding dental arch curve is described according to above-mentioned denture.
The dental arch curve determined on above-mentioned target two dimensional image can be applied on each two-dimentional oral cavity CBCT image, make it is above-mentioned each two
Dimension oral cavity CBCT image arcus dentalis superior curves are determined.
S30, is equidistantly sampled on the dental arch curve of each two-dimentional oral cavity CBCT image respectively, obtains each two-dimentional oral cavity
Each multiple sampled point of two-dimentional oral cavity CBCT picture positions identical is defined as one group and adopted by multiple sampled points on CBCT images
Sampling point；
Equidistantly sampled on the dental arch curve of above-mentioned two-dimentional oral cavity CBCT images, first sampled point can be dental arch
One end points of curve, last sampled point can be between another end points of dental arch curve, two sampled points of arbitrary neighborhood
Apart from equal, any one sampled point on a two-dimentional oral cavity CBCT image on other each two-dimentional oral cavity CBCT images
Existence position (position on corresponding dental arch curve) identical sampled point.On a dental arch curve, two neighboring sampled point it
Between distance be not more than 2 pixels of two-dimentional oral cavity CBCT images or two-dimentional oral cavity CBCT images, to ensure between each sampled point
Gray-value variation be smooth transition.
S40, obtains the corresponding sampling matrix of each group sampled point, is weighted forward projection behaviour to each sampling matrix respectively
Make, obtain multiple weighting matrixs；
Above-mentioned steps can set up each group sampling by obtaining pixel point feature of the dental arch curve on sample point normal
The corresponding sampling matrix of point, makes resulting sampling matrix as far as possible comprising the tooth structure on each two-dimentional oral cavity CBCT image
Information.
After the corresponding sampling matrix of each group sampled point is obtained, the corresponding pixel of each sampling matrix can be built respectively
Battle array, it is determined that transmitting reference point, the pixel point feature that the ray sent by above-mentioned transmitting reference point is passed through determines weight coefficient,
The pixel value of the pixel passed through using above-mentioned weight coefficient to ray is weighted summation operation, to be weighted accordingly
Matrix.
S50, each weighting matrix is spliced in sequence, and the oral cavity CBCT images are obtained according to splicing result
Panoramic picture.
The order of above-mentioned splicing weighting matrix is arrangement of the sampled point on dental arch curve corresponding to each weighting matrix
Sequence of positions.The corresponding three-dimensional data battle array of corresponding oral cavity structure can be obtained after each weighting matrix is spliced in sequence
This splicing result, the splicing result can characterize the pixel value tag of each image layer pixels point of oral cavity structure, according to above-mentioned
Panoramic picture constructed by splicing result intactly can clearly be showed to oral cavity structure, more meet human eye observation's model.
The panoramic picture acquisition methods for the oral cavity CBCT images that the present embodiment is provided, by multiple continuous two-dimentional oral cavities
Equidistantly sampled on the dental arch curve of CBCT images, multiple sampled points on each two-dimentional oral cavity CBCT images are obtained, by each
The multiple sampled points of two-dimentional oral cavity CBCT picture positions identical are defined as one group of sampled point, and then it is corresponding to obtain each group sampled point
Sampling matrix, to obtain corresponding weighting matrix, then each weighting matrix is spliced in sequence, is obtained according to splicing result
The panoramic picture of the oral cavity CBCT images is taken, resulting panoramic picture covers each above-mentioned two-dimentional oral cavity CBCT images institute
The feature of carrying, with higher accuracy, more conforms to the Visual Observations Observations characteristic of human eye.
In one embodiment, the process of the corresponding sampling matrix of above-mentioned acquisition each group sampled point can include：
Step 311, for any one group of sampled point, obtained wherein on the two-dimentional oral cavity CBCT images where a sampled point
The normal of the sampled point is taken, centered on the sampled point, the normal of setpoint distance is respectively taken to the sampled point both sides, goal method is obtained
Line segment, one-dimensional matrix is generated according to the pixel value of pixel on the goal method line segment；Wherein, each yuan of the one-dimensional matrix
Each pixel of element and goal method line segment is in correspondence with each other；First element value of the one-dimensional matrix is on goal method line segment
Positioned at the corresponding pixel value of the outermost pixel in oral cavity；
Fractional-sample point on one two-dimentional oral cavity CBCT image arcus dentalis superior curve may be referred to shown in Fig. 2, mark in Fig. 2
47th point (sampled point), and the 47th corresponding normal of point, can centered on the 47th point, to the sampled point both sides
(on the inside of dental arch curve, i.e., on the inside of oral cavity, and on the outside of dental arch curve) respectively takes the normal of setpoint distance, obtains goal method line segment,
Generate the corresponding one-dimensional matrix of the 47th point.Above-mentioned setpoint distance can carry out true according to the characteristic of oral cavity structure interior tooth toothing
It is fixed, such as it is defined as 10 pixels.In the corresponding one-dimensional matrix of 47th point, first element value is goal method line segment
The upper corresponding pixel value of pixel positioned at oral cavity outermost (dental arch curve outermost), second element value is target normal
Duan Shangcong oral cavities outermost starts the corresponding pixel value of second pixel point, by that analogy, and last element value is target
The upper corresponding pixel value of pixel in oral cavity most inner side (dental arch curve most inner side) of method line segment.
Step 312, the step 311 is repeated, until it is corresponding to obtain each sampled point difference in this group of sampled point
One-dimensional matrix, by each one-dimensional matrix, according to two-dimentional oral cavity CBCT images where corresponding sampled point, (i.e. dental arch where sampled point is bent
Line) arrangement along being overlapped, obtain the corresponding sampling matrix of this group of sampled point；
If setpoint distance is a pixel, the line number (height) of above-mentioned sampling matrix is continuous two-dimentional oral cavity CBCT images
Number, columns (width) be (2a+1).
Step 313, do not obtain each group sampled point of sampling matrix for other respectively, perform successively the step 311 and
Step 312, until obtaining each group sampled point distinguishes corresponding sampling matrix.
Sampling matrix acquired in the present embodiment can include each two-dimentional oral cavity CBCT images upper tooth toothing as far as possible
Characteristic information, with higher precision.
In one embodiment, it is above-mentioned to be weighted forward projection operation to each sampling matrix respectively, obtain multiple add
The process of weight matrix can include：
Step 321, the corresponding pixel-matrix of any one sampling matrix is built, the center row of the pixel-matrix is obtained,
Set in the center row and transmitting reference point S is taken on the extended line of side, by the transmitting reference point S and the pixel-matrix most
Line between latter first pixel of row is defined as just ray, by the transmitting reference point S and the pixel-matrix most
The latter line arranged between last pixel is defined as last ray；
If each element of above-mentioned sampling matrix is the pixel value corresponding to respective pixel point, can according to above-mentioned pixel value
To build the corresponding pixel-matrix of sampling matrix, above-mentioned pixel-matrix may be referred to shown in Fig. 3, and 81 represent pixel-matrix in figure.
Set in the center row of pixel-matrix and transmitting reference point S is taken on the extended line of side, obtained from above-mentioned transmitting reference point S to pixel
The a plurality of ray that paroxysm goes out, wherein first ray (first ray) is the ray by last first pixel of row, finally
One ray (last ray) is the ray that last pixel is arranged by last.The middle behavior of above-mentioned pixel-matrix is in
The one-row pixels point (sampling matrix line number is odd number) in pixel-matrix centre position, or in pixel-matrix centre position
Center line row between two row pixels (sampling matrix line number is even number).
Step 322, a plurality of ray sent between the just ray and last ray by the transmitting reference point S is obtained, such as
Line1, line2 ... ..., line (R-1), lineR；Wherein, line1 is first ray, and lineR is last ray, line2 to line
(R-1) it is a plurality of ray between first ray and last ray, R is the positive integer more than 2, that is, is sent from transmitting reference point S
Penetrate number of lines；Angle between two rays of arbitrary neighborhood is θ/(R-1), and θ is the angle between first ray and last ray；
Step 323, the pixel that any one ray (such as line1) sequentially passes through is recognized, obtains each pixel difference
The corresponding pixel value p (1) of the pixel of corresponding pixel value, i.e., first, the corresponding pixel value p of second pixel point
(2) ... ..., the corresponding pixel value p (d+1) ... ... of (d+1) individual pixel, the corresponding pixel value p of (2d+1) individual pixel
(2d+1), is weighted to each pixel value and averagely obtains the corresponding weighted average of the ray：Its
In, weight coefficient calculation formula is：W (i)=1/ (1+ | d+1-i |), i is just whole more than or equal to 1 and less than or equal to (2d+1)
Number；It is above-mentioned respectively to take the setpoint distance in the normal of setpoint distance to be d length in pixels to corresponding sampled point both sides；If from penetrating
The ray that line transmitting reference point S is sent is worn also cross two pixels in the same row of sampling matrix, now a recording ray
The length for the two pixels crossed most long that pixel；
Above-mentioned steps 323 can recognize the pixel that corresponding ray is sequentially passed through according to biggest advantage of light track algorithm.FormulaIn, subscript A1 represents the positive sampling matrix for obtaining weighting matrix, such as first sampling matrix, PA11 represents
The corresponding weighted average of corresponding ray in the sampling matrix.
Step 324, step is performed respectively for not obtaining other each bar rays (such as line2 to lineR) of weighted average
Rapid 323, obtain the corresponding weighted average P of the corresponding each bar ray of the pixel-matrixA12, PA13 ... ..., PA1R, by each
Weighted average is arranged in column matrix according to corresponding ray order, obtains the corresponding weighting matrix of the sampling matrix；On wherein
State PA12 be the corresponding weighted averages of line2, wherein above-mentioned PA13 be the corresponding weighted averages of line3, by that analogy, PA1R
For the corresponding weighted averages of lineR；Above-mentioned weighted average PA12, PA13 ... ..., PA1R putting in order in weighting matrix
Ray position information corresponding with each weighted average is consistent, i.e., just ray line1 weighted average PA11 is weighting matrix
First element (uppermost element value), line2 weighted average PA12 be second element of weighting matrix, last ray
LineR weighted average PA1R is last element of weighting matrix；
Step 325, the sampling matrix for not obtaining weighting matrix for other respectively performs step 321 to step 324, obtains
The corresponding weighting matrix of each sampling matrix.
The present embodiment obtains the corresponding weighting square of each sampling matrix by more specific weighting forward projection operating process
Battle array, with higher accuracy.
In one embodiment, it is above-mentioned to recognize that the process of dental arch curve includes on the target two dimensional image：
The denture in the target two dimensional image is recognized, respective objects X-Y scheme will be defined as through denture curve
As upper dental arch curve.
The present embodiment can be automatically generated a curve by computer, by adjusting shape, the length of curve, be passed through
Denture in two-dimentional oral cavity CBCT images, realizes the determination of above-mentioned dental arch curve.
In one embodiment, it is above-mentioned to recognize that the process of dental arch curve includes on the target two dimensional image：Identification institute
State the denture in target two dimensional image, multiple seed points selected in the denture, by the target two dimensional image by each
The smooth curve of individual seed point is defined as the dental arch curve of the target two dimensional image.
The present embodiment can select a series of seed points by way of mouse is clicked on image in denture,
The curve of a continuous and derivable is obtained using curve-fitting method, to obtain corresponding dental arch curve.
In one embodiment, the sampled point that the order of above-mentioned splicing weighting matrix can be corresponding to each weighting matrix
Arrangement position order on dental arch curve.
The present embodiment may further ensure that the accuracy of acquired panoramic picture.
In one embodiment, the distance between two neighboring sampled point is less than or equal to 2 on above-mentioned dental arch curve
Pixel.
In the present embodiment, the distance between two neighboring sampled point is less than or equal to 2 pixels on dental arch curve, can be with
Ensure that the gray-value variation between sampled point is smooth transition.
In one embodiment, so that Pixel Dimensions is 512*512 multiple continuous two-dimentional oral cavity CBCT images as an example, obtain
The process of corresponding panoramic picture can include：
(1) many continuous two-dimentional oral cavity CBCT images containing tooth structure, are obtained, 3-D view, every layer of figure is constituted
Picture matrix size is 512*512, and the length for remembering each pixel is unit 1, and one has 512 tomographic images.
(2) one layer of CBCT two-dimensional image I as shown in Figure 4, is selected, if level number is the 308th layer, it is determined that wherein one dental arch
Curve Curve, the method for determination can be：Along the direction of dental arch, image is clicked on by mouse, a series of seed points (ginseng is determined
Examine shown in Fig. 5), four adjacent points can be sequentially connected using cubic B-spline algorithm, smooth curve as shown in Figure 6 is generated.
(3) normal direction for obtaining curve up-sampling point, is calculated according to above-mentioned curve, sampled point is designated as P1, P2 ... ...,
PN, N are the number of sampled point, and N=617 is denoted as the corresponding normal of each sampled point for F1, F2 ... ..., FN.47th sampling
The normal direction that point is asked for may be referred to shown in Fig. 2.
(4), setpoint distance A=10, unit be the length in pixels of unit 1, i.e., 10, the point centered on the 47th sampled point,
10 length in pixels are respectively asked for along its both sides direction on normal, are obtained in the distances of 2*A+1 altogether for including sampled point
All pixels point, forms an one-dimensional row matrix, and the order of element from left to right is that 2*A+1 distances are interior in image in row matrix
All pixels put in order outside oral cavity to interior.According to the stacking order of CBCT 3-D views, according to the 47th point of processing
Mode, many one-dimensional matrixes of other tomographic images can be obtained, and enumerate as two-dimensional matrix, width is 2*A+1, is highly
512 (because having 512 width CBCT images), are denoted as two-dimensional matrix for A1；
(5), for other sampled points on curve, the operation of repeat step (4) can obtain corresponding two-dimensional matrix altogether
For A1, A2 ... ..., AN.
(6), by taking the 47th point on curve as an example, the weighting forward projection of its corresponding matrix A 47 is calculated, column matrix is obtained
L47 (weighting matrix), circular is as follows：
(6.1) for the corresponding pixel-matrix of matrix A 47 (diagram matrix 47), center row position is calculated, is 512/2=
256, with reference to shown in Fig. 7, on the extended line on the left of center row, it is D=235, S to take point S, distance matrix L47 a left side edge
The angle theta that point and last row of matrix first pixel T1 and last pixel T2 line ST1 and ST2 are formed,
By can be calculated θ=90 degree；
(6.2) using S points as ray origin, a plurality of equally spaced ray is formed in the angular range that ST1 and ST2 are formed
Line1, line2 ... ..., lineR, line1 is exactly ST1, and lineR is exactly ST2, R to penetrate number of lines, then adjacent two rays it
Between angle be 1 degree, penetrate number of lines R=91；
(6.3) for every ray, according to biggest advantage of light track algorithm, it can calculate and obtain ray through which pixel；
(6.4) remember that the pixel point value that the 1st article of ray passes through is respectively p (1), p (2) ... ..., p (d+1) ..., p (2d+
1), then the d+1 pixel is exactly the pixel under corresponding curve in CBCT images.Using the point as central point, to p (1),
P (2) ... ..., p (d+1) ... ..., p (2d+1) pixel value are weighted averageWeight coefficient is calculated
Formula is：W (i)=1/ (1+ | d+1-i |).The weighted average that other rays are formed is designated as PA472, PA473 ..., PA47R,
And sort in column direction, column matrix is obtained, such as the 47th corresponding weighting matrix of point is：
(7), according to the operating procedure of step 6, the other matrix As 1, A2 ... ... of calculating, AN weighting forward projection, successively
Column matrix L2 ... ..., LN are obtained, by column matrix L1, L2 ... ..., (corresponding sampled point is in dental arch according to order from left to right by LN
Putting in order on curve) it is stitched together successively, obtain panorama sketch matrix [L1, L2 ... ..., LN], the panorama obtained with this
Image (tooth layout viewing) may be referred to shown in Fig. 8.
With reference to shown in Fig. 9, Fig. 9 obtains system architecture signal for the panoramic picture of the oral cavity CBCT images of one embodiment
Figure, including：
Selecting module 10, for selecting one to contain tooth structure image in multiple continuous two-dimentional oral cavity CBCT images
Two-dimentional oral cavity CBCT images be used as target two dimensional image；
Identification module 20, for recognizing dental arch curve on the target two dimensional image, according to the target two dimensional image
On dental arch curve determine the dental arch curve of each two-dimentional oral cavity CBCT image；
Sampling module 30, for equidistantly being sampled on the dental arch curve of each two-dimentional oral cavity CBCT image respectively, is obtained
Multiple sampled points onto each two-dimentional oral cavity CBCT images, by each multiple sampled point of two-dimentional oral cavity CBCT picture positions identical
It is defined as one group of sampled point；
Acquisition module 40, for obtaining the corresponding sampling matrix of each group sampled point, is added to each sampling matrix respectively
Forward projection operation is weighed, multiple weighting matrixs are obtained；
Concatenation module 50, for each weighting matrix to be spliced in sequence, the mouth is obtained according to splicing result
The panoramic picture of chamber CBCT images.
The panoramic picture for the oral cavity CBCT images that the present invention is provided obtains the oral cavity CBCT images that system is provided with the present invention
Panoramic picture acquisition methods correspond, the oral cavity CBCT images panoramic picture acquisition methods embodiment illustrate
Technical characteristic and its advantage are obtained the embodiment of system suitable for the panoramic picture of oral cavity CBCT images, hereby sound
It is bright.
Based on example as described above, a kind of computer-readable recording medium is also provided in one embodiment, stored thereon
There is computer program, the computer program realizes that the panoramic picture of CBCT images in oral cavity as described above is obtained when being executed by processor
Take method.
One of ordinary skill in the art will appreciate that realize all or part of flow in above-described embodiment method, being can be with
The hardware of correlation is instructed to complete by computer program, described computer program can be stored in a non-volatile calculating
In machine read/write memory medium, in such as embodiment of the present invention, the program can be stored in the storage medium of computer system, and by
At least one computing device in the computer system, to realize the flow for including the embodiment such as above-mentioned each method.Wherein,
Described storage medium can be magnetic disc, CD, read-only memory (Read-Only Memory, ROM) or random storage note
Recall body (Random Access Memory, RAM) etc..
Based on example as described above, with reference to shown in Figure 10, the present invention also provides a kind of computer equipment 60, the computer
Equipment includes memory 61, processor 62 and is stored in the computer program that can be run on memory 62 and on processor 61,
The processor 61 realizes the panorama sketch of any one oral cavity CBCT images in each embodiment as described above when performing described program
As acquisition methods.
Above computer equipment 60 can including computer etc. Intelligent treatment equipment.One of ordinary skill in the art will appreciate that
The computer program that memory 61 is stored, with the description phase in the panoramic picture acquisition methods embodiment of above-mentioned oral cavity CBCT images
Correspondence, processor 62 can also be used to perform other executable instructions that memory 61 is stored.
Each technical characteristic of embodiment described above can be combined arbitrarily, to make description succinct, not to above-mentioned reality
Apply all possible combination of each technical characteristic in example to be all described, as long as however, the combination of these technical characteristics is not deposited
In contradiction, the scope of this specification record is all considered to be.
Embodiment described above only expresses the several embodiments of the present invention, and it describes more specific and detailed, but simultaneously
Can not therefore it be construed as limiting the scope of the patent.It should be pointed out that coming for one of ordinary skill in the art
Say, without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to the protection of the present invention
Scope.Therefore, the protection domain of patent of the present invention should be determined by the appended claims.
Claims (10)
1. a kind of panoramic picture acquisition methods of oral cavity CBCT images, it is characterised in that comprise the following steps：
A two-dimentional oral cavity CBCT image containing tooth structure image is selected in multiple continuous two-dimentional oral cavity CBCT images
It is used as target two dimensional image；
Dental arch curve is recognized on the target two dimensional image, each is determined according to the dental arch curve on the target two dimensional image
The dental arch curve of two-dimentional oral cavity CBCT images；
Equidistantly sampled on the dental arch curve of each two-dimentional oral cavity CBCT image respectively, obtain each two-dimentional oral cavity CBCT images
On multiple sampled points, each multiple sampled point of two-dimentional oral cavity CBCT picture positions identical is defined as one group of sampled point；
The corresponding sampling matrix of each group sampled point is obtained, forward projection operation is weighted to each sampling matrix respectively, obtains
Multiple weighting matrixs；
Each weighting matrix is spliced in sequence, the panorama sketch of the oral cavity CBCT images is obtained according to splicing result
Picture.
2. the panoramic picture acquisition methods of CBCT images in oral cavity according to claim 1, it is characterised in that the acquisition is each
The process of the corresponding sampling matrix of group sampled point includes：
Step 311, for any one group of sampled point, being obtained wherein on the two-dimentional oral cavity CBCT images where a sampled point should
The normal of sampled point, centered on the sampled point, the normal of setpoint distance is respectively taken to the sampled point both sides, target normal is obtained
Section, one-dimensional matrix is generated according to the pixel value of pixel on the goal method line segment；Wherein, each element of the one-dimensional matrix
With each pixel of goal method line segment in correspondence with each other；First element value of the one-dimensional matrix is that goal method line segment is upper
In the corresponding pixel value of the outermost pixel in oral cavity；
Step 312, the step 311 is repeated, until it is corresponding one-dimensional to obtain each sampled point difference in this group of sampled point
Matrix, each one-dimensional matrix is somebody's turn to do according to the arrangement of two-dimentional oral cavity CBCT images where corresponding sampled point along being overlapped
The corresponding sampling matrix of group sampled point；
Step 313, do not obtain each group sampled point of sampling matrix for other respectively, the step 311 and step are performed successively
312, until obtaining each group sampled point distinguishes corresponding sampling matrix.
3. the panoramic picture acquisition methods of CBCT images in oral cavity according to claim 1, it is characterised in that described right respectively
Each sampling matrix is weighted forward projection operation, and obtaining the process of multiple weighting matrixs includes：
Step 321, the corresponding pixel-matrix of any one sampling matrix is built, the center row of the pixel-matrix is obtained, in institute
Transmitting reference point S is taken on the extended line for stating center row setting side, by last of the transmitting reference point S and the pixel-matrix
Line between first pixel of row is defined as just ray, by last of the transmitting reference point S and the pixel-matrix
Arrange the line between last pixel and be defined as last ray；
Step 322, a plurality of ray sent between the just ray and last ray by the transmitting reference point S is obtained；Wherein, appoint
The angle between adjacent two rays of anticipating is θ/(R-1), and θ is the angle between first ray and last ray, and R is transmitting reference point S
Number of lines is penetrated to what the pixel-matrix was sent；
Step 323, the pixel that any one ray is sequentially passed through is recognized, the corresponding picture of wherein first pixel is obtained respectively
Element value p (1), the corresponding pixel value p (2) ... ... of second pixel point, the corresponding pixel value p (d+ of (d+1) individual pixel
1) ... ..., the corresponding pixel value p (2d+1) of (2d+1) individual pixel, is weighted to each pixel value and averagely obtains this and penetrate
The corresponding weighted average of line：Wherein, weight coefficient calculation formula is：W (i)=1/ (1+ | d+1-i
|), i is the positive integer more than or equal to 1 and less than or equal to (2d+1)；
Step 324, step 323 is performed respectively for not obtaining other each bar rays of weighted average, obtain the pixel
The corresponding weighted average of the corresponding each bar ray of battle array, by each weighted average according to corresponding ray order arrangement square in column
Battle array, obtains the corresponding weighting matrix of the sampling matrix；
Step 325, the sampling matrix for not obtaining weighting matrix for other respectively performs step 321 to step 324, obtains each
The corresponding weighting matrix of sampling matrix.
4. the panoramic picture acquisition methods of CBCT images in oral cavity according to claim 1, it is characterised in that described described
Recognize that the process of dental arch curve includes on target two dimensional image：
The denture in the target two dimensional image is recognized, will be defined as through denture curve on respective objects two dimensional image
Dental arch curve.
5. the panoramic picture acquisition methods of CBCT images in oral cavity according to claim 1, it is characterised in that described described
Recognize that the process of dental arch curve includes on target two dimensional image：
The denture in the target two dimensional image is recognized, multiple seed points are selected in the denture, by the target X-Y scheme
It is defined as the dental arch curve of the target two dimensional image by the smooth curve of each seed point as on.
6. the panoramic picture acquisition methods of CBCT images in oral cavity according to claim 1, it is characterised in that the splicing adds
The order of weight matrix is arrangement position order of the sampled point on dental arch curve corresponding to each weighting matrix.
7. the panoramic picture acquisition methods of the oral cavity CBCT images according to any one of claim 1 to 6, it is characterised in that
The distance between two neighboring sampled point is less than or equal to 2 pixels on the dental arch curve.
8. a kind of panoramic picture of oral cavity CBCT images obtains system, it is characterised in that including：
Selecting module, for selecting a two dimension containing tooth structure image in multiple continuous two-dimentional oral cavity CBCT images
Oral cavity CBCT images are used as target two dimensional image；
Identification module, for recognizing dental arch curve on the target two dimensional image, according to the tooth on the target two dimensional image
Bow line determines the dental arch curve of each two-dimentional oral cavity CBCT image；
Sampling module, for equidistantly being sampled on the dental arch curve of each two-dimentional oral cavity CBCT image respectively, obtains each two
Multiple sampled points on the CBCT images of oral cavity are tieed up, each multiple sampled point of two-dimentional oral cavity CBCT picture positions identical is defined as
One group of sampled point；
Acquisition module, for obtaining the corresponding sampling matrix of each group sampled point, each sampling matrix is weighted respectively before to
Projection operation, obtains multiple weighting matrixs；
Concatenation module, for each weighting matrix to be spliced in sequence, the oral cavity CBCT is obtained according to splicing result
The panoramic picture of image.
9. a kind of computer-readable recording medium, is stored thereon with computer program, it is characterised in that the computer program is located
Manage the panoramic picture acquisition methods that the oral cavity CBCT images as described in claim 1 to 7 any one are realized when device is performed.
10. a kind of computer equipment, including memory, processor and storage are on a memory and the meter that can run on a processor
Calculation machine program, it is characterised in that realized during the computing device described program as described in claim 1 to 7 any one
The panoramic picture acquisition methods of oral cavity CBCT images.
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107798656A (en) * | 2017-11-09 | 2018-03-13 | 南京齿贝犀科技有限公司 | A kind of oral cavity Panorama Mosaic method based on range sensor and gyroscope |
| CN108597004A (en) * | 2018-05-08 | 2018-09-28 | 南京齿贝犀科技有限公司 | Occlusal surfaces of teeth Panorama Mosaic method based on Local Optimization Algorithm |
| CN108711177A (en) * | 2018-05-15 | 2018-10-26 | 南方医科大学口腔医院 | The fast automatic extracting method of volume data arch wire after a kind of oral cavity CBCT is rebuild |
| CN109727296A (en) * | 2018-12-27 | 2019-05-07 | 影为医疗科技(上海)有限公司 | Curved surface projection display methods, system, computer media and the equipment of root canal inner cavity |
| CN111110264A (en) * | 2019-12-28 | 2020-05-08 | 常州博恩中鼎医疗科技有限公司 | Optimization method of dental CBCT panoramic motion trajectory |
| CN111161147A (en) * | 2019-12-27 | 2020-05-15 | 常州博恩中鼎医疗科技有限公司 | Dental CBCT image panoramic stitching method based on anterior teeth correction |
| CN111553941A (en) * | 2020-04-30 | 2020-08-18 | 赤峰学院附属医院 | Method and device for synthesizing panoramic view of oral cavity of user and electronic equipment |
| CN111833244A (en) * | 2019-04-11 | 2020-10-27 | 深圳市深图医学影像设备有限公司 | Dental panoramic image generation method and device and computer readable storage medium |
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| EP4279022A1 (en) | 2022-05-16 | 2023-11-22 | Institut Straumann AG | Manufacturing of orthodontic devices based on standardized scan representations |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101950430A (en) * | 2010-09-23 | 2011-01-19 | 北京大学 | Three-dimensional tooth reconstruction method based on panoramic tomograph |
| CN105894444A (en) * | 2016-03-31 | 2016-08-24 | 深圳市菲森科技有限公司 | Method and device for generating dental panoramic image on the basis of CBCT image |
| CN105982691A (en) * | 2015-01-30 | 2016-10-05 | 合肥美亚光电技术股份有限公司 | Method and device for shooting local CT (computerized tomography) images |
| US20170007191A1 (en) * | 2015-07-02 | 2017-01-12 | Cefla Societä Cooperativa | Method and apparatus for acquiring panoramic and CBCT volumetric radiographies |
| CN106846307A (en) * | 2017-01-19 | 2017-06-13 | 深圳市深图医学影像设备有限公司 | Image processing method and device based on pencil-beam computed tomography |
-
2017
- 2017-06-20 CN CN201710470864.3A patent/CN107301622B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101950430A (en) * | 2010-09-23 | 2011-01-19 | 北京大学 | Three-dimensional tooth reconstruction method based on panoramic tomograph |
| CN105982691A (en) * | 2015-01-30 | 2016-10-05 | 合肥美亚光电技术股份有限公司 | Method and device for shooting local CT (computerized tomography) images |
| US20170007191A1 (en) * | 2015-07-02 | 2017-01-12 | Cefla Societä Cooperativa | Method and apparatus for acquiring panoramic and CBCT volumetric radiographies |
| CN105894444A (en) * | 2016-03-31 | 2016-08-24 | 深圳市菲森科技有限公司 | Method and device for generating dental panoramic image on the basis of CBCT image |
| CN106846307A (en) * | 2017-01-19 | 2017-06-13 | 深圳市深图医学影像设备有限公司 | Image processing method and device based on pencil-beam computed tomography |
Non-Patent Citations (1)
| Title |
|---|
| 万俊等: "口腔全景锥形束CT图像重建算法", 《中国医学物理学杂志》 * |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107798656A (en) * | 2017-11-09 | 2018-03-13 | 南京齿贝犀科技有限公司 | A kind of oral cavity Panorama Mosaic method based on range sensor and gyroscope |
| CN108597004A (en) * | 2018-05-08 | 2018-09-28 | 南京齿贝犀科技有限公司 | Occlusal surfaces of teeth Panorama Mosaic method based on Local Optimization Algorithm |
| CN108711177A (en) * | 2018-05-15 | 2018-10-26 | 南方医科大学口腔医院 | The fast automatic extracting method of volume data arch wire after a kind of oral cavity CBCT is rebuild |
| CN108711177B (en) * | 2018-05-15 | 2022-04-01 | 南方医科大学口腔医院 | Method for quickly and automatically extracting dental arch line of oral CBCT reconstructed posterior body data |
| CN109727296B (en) * | 2018-12-27 | 2023-03-10 | 影为医疗科技(上海)有限公司 | Method, system, computer medium and equipment for curved surface projection display of root canal inner cavity |
| CN109727296A (en) * | 2018-12-27 | 2019-05-07 | 影为医疗科技(上海)有限公司 | Curved surface projection display methods, system, computer media and the equipment of root canal inner cavity |
| CN111833244A (en) * | 2019-04-11 | 2020-10-27 | 深圳市深图医学影像设备有限公司 | Dental panoramic image generation method and device and computer readable storage medium |
| CN111161147A (en) * | 2019-12-27 | 2020-05-15 | 常州博恩中鼎医疗科技有限公司 | Dental CBCT image panoramic stitching method based on anterior teeth correction |
| CN111161147B (en) * | 2019-12-27 | 2023-08-22 | 常州博恩中鼎医疗科技有限公司 | Panoramic stitching method of dental CBCT image based on anterior tooth correction |
| CN111110264A (en) * | 2019-12-28 | 2020-05-08 | 常州博恩中鼎医疗科技有限公司 | Optimization method of dental CBCT panoramic motion trajectory |
| CN111110264B (en) * | 2019-12-28 | 2022-06-17 | 常州博恩中鼎医疗科技有限公司 | Optimization method of dental CBCT panoramic motion trajectory |
| CN111553941A (en) * | 2020-04-30 | 2020-08-18 | 赤峰学院附属医院 | Method and device for synthesizing panoramic view of oral cavity of user and electronic equipment |
| CN114463407B (en) * | 2022-01-19 | 2023-02-17 | 西安交通大学口腔医院 | System for realizing oral cavity shaping simulation display by combining 3D image with feature fusion technology |
| CN114463407A (en) * | 2022-01-19 | 2022-05-10 | 西安交通大学口腔医院 | System for realizing oral cavity shaping simulation display by combining 3D image with feature fusion technology |
| EP4279022A1 (en) | 2022-05-16 | 2023-11-22 | Institut Straumann AG | Manufacturing of orthodontic devices based on standardized scan representations |
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