CN114723765B - Automatic extraction method of dental archwire - Google Patents
Automatic extraction method of dental archwire Download PDFInfo
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- 238000000605 extraction Methods 0.000 title claims abstract description 23
- 210000002455 dental arch Anatomy 0.000 claims abstract description 23
- 238000000034 method Methods 0.000 claims abstract description 22
- 230000009466 transformation Effects 0.000 claims abstract description 10
- 230000000877 morphologic effect Effects 0.000 claims abstract description 6
- 238000006243 chemical reaction Methods 0.000 claims description 14
- 239000000284 extract Substances 0.000 claims description 9
- 238000002591 computed tomography Methods 0.000 claims description 6
- 238000010586 diagram Methods 0.000 claims description 6
- 238000005070 sampling Methods 0.000 claims description 6
- 239000007943 implant Substances 0.000 claims description 4
- 238000004458 analytical method Methods 0.000 claims description 3
- 210000003128 head Anatomy 0.000 claims description 3
- 210000000214 mouth Anatomy 0.000 claims description 3
- 210000001202 rhombencephalon Anatomy 0.000 claims description 3
- 230000008569 process Effects 0.000 abstract description 7
- 230000006978 adaptation Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 239000004053 dental implant Substances 0.000 description 1
- 238000002513 implantation Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000001356 surgical procedure Methods 0.000 description 1
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61C—DENTISTRY; APPARATUS OR METHODS FOR ORAL OR DENTAL HYGIENE
- A61C8/00—Means to be fixed to the jaw-bone for consolidating natural teeth or for fixing dental prostheses thereon; Dental implants; Implanting tools
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- A61B2034/101—Computer-aided simulation of surgical operations
- A61B2034/105—Modelling of the patient, e.g. for ligaments or bones
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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- A61B2034/107—Visualisation of planned trajectories or target regions
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- A61B2034/108—Computer aided selection or customisation of medical implants or cutting guides
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Abstract
The invention provides an automatic extraction method of dental archwires, which comprises the following steps: carrying out crown maximum intensity projection on the crown CT slice sequence, and carrying out pixel statistics to generate a crown maximum intensity projection histogram; fitting normal distribution to obtain a binarization threshold; binarizing the coronal maximum intensity projection graph, and counting the number of pixels along a v axis to obtain a CT slice range of axial maximum intensity projection; and carrying out axial maximum intensity projection on the determined axial CT slice, generating an axial maximum intensity projection histogram, carrying out subsequent processing such as prescribing and the like, and extracting the final dental archwire. The whole dental arch line extraction process is automatically carried out, and the specification of the histogram is carried out by using the template in the middle process, so that the parameters used in the process of regional growth, morphological operation and gamma transformation have strong universality. Therefore, the whole method for extracting the dental arch line has strong real-time performance, high robustness and high accuracy and is fully and automatically carried out.
Description
Technical Field
The invention belongs to the technical field of machine vision, and particularly relates to an automatic extraction method of dental archwires.
Background
At present, with the continuous improvement of the living standard of people, dental implant surgery is adopted by more and more patients. Before the implantation operation starts, the position of the teeth to be implanted needs to be planned firstly, and the planning method comprises the following steps: it is desirable to develop the archwire into a panoramic view for convenient viewing by the dentist to determine the location where the implant is to be implanted. The panoramic view needs to be unfolded along the dental archwire at this time, so that the dental archwire needs to be automatically extracted first in the preoperative planning. The existing method comprises the following steps: the method directly depends on the clinical experience of an stomatologist, points are selected at the positions of dental archwires, then dental implant software automatically fits the dental archwires according to the points selected by the doctor, the method has high requirements on the clinical experience of the doctor, the point selection time of the doctor is wasted, and the dental archwire extraction efficiency is low.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention provides an automatic extraction method for dental archwires, which can effectively solve the problems.
The technical scheme adopted by the invention is as follows:
The invention provides an automatic extraction method of dental archwires, which comprises the following steps:
step S1, respectively performing crown CT scanning and axial CT scanning on a tooth area of a head to respectively obtain a crown CT slice sequence and an axial CT slice sequence; wherein, the coronal direction refers to: from hindbrain scoop to face direction, namely: from the back to the front; the axial direction refers to the top-down direction;
coronal CT slice sequences refer to: each coronal CT slice is overlapped along the front-back direction; each coronal CT slice is a vertical slice;
Axial CT slice sequences refer to: each axial CT slice is overlapped along the up-down direction; each axial CT slice is a horizontal slice;
step S2, carrying out crown maximum intensity projection on the crown CT slice sequence to obtain a crown maximum intensity projection diagram; the crown maximum intensity projection graph is a two-dimensional plane graph;
Step S3, counting pixels of the crown maximum intensity projection graph to generate a crown maximum intensity projection histogram; wherein, the abscissa of the coronal maximum intensity projection histogram is a pixel value of 0-256, and the ordinate is: the number of occurrences of each pixel value in the coronal maximum intensity projection map;
Fitting normal distribution to the crown maximum intensity projection histogram to obtain a mean mu 0 and a variance sigma 0 after normal distribution fitting; from the mean μ 0 and the variance σ 0, the binarization threshold threshHold is obtained using the following formula:
threshHold＝μ0+kσ0
wherein: k is an empirical coefficient;
step S4, binarizing the crown maximum intensity projection image generated in the step S2 by using the binarization threshold threshHold generated in the step S3, so as to generate a crown binarized image;
The binarization method comprises the following steps: for each pixel point in the coronal maximum intensity projection graph, if the pixel value is less than a binarization threshold threshHold, changing the pixel value to 0; otherwise, the pixel value is changed to 1;
S5, the image coordinate system of the coronal binarized image is a u-v coordinate system; wherein the v axis is in the vertical direction; the u-axis is the direction perpendicular to the v-axis in the image;
And carrying out statistics on the number of pixels along the v axis of the coronal binarized image, namely: drawing a straight line L1 parallel to a u axis at a v=1 position in the coronal binarized image, and counting the number N1 of pixel points, with the pixel value of 1, of the coronal binarized image, through which the straight line L1 passes; drawing a straight line L2 parallel to the u axis at the position of v=2, and counting the number N2 of pixel points with the pixel value of 1 of the coronal binarized image through which the straight line L2 passes; according to the classification, counting the number of pixels in the v-axis direction of the coronal binarized image is completed, and a plurality of discrete points in a coordinate system with the abscissa being the v-axis and the ordinate being the number N of pixel points are obtained; fitting the normal distribution of each obtained discrete point to obtain a mean mu 1 and a variance sigma 1 after fitting the normal distribution;
According to the mean mu 1 and the variance sigma 1 after normal distribution fitting, the following formula is adopted to obtain a CT slice starting position downslice entering the axial maximum intensity projection and a CT slice ending position upSlice entering the axial maximum intensity projection:
upSlice＝μ1+kuσ1
downSlice＝μ1-kdσ1
wherein:
k u and k d are both empirical coefficients;
S6, selecting all axial CT slices with slice numbers of downSlice-upSlice from top to bottom in the axial CT slice sequence obtained in the step S1 to form an axial CT slice sequence set;
performing axial maximum intensity projection on the axial CT slice sequence set to obtain an axial maximum intensity projection diagram;
S7, counting pixels of the axial maximum intensity projection graph to generate an axial maximum intensity projection histogram; wherein, the abscissa of the axial maximum intensity projection histogram is a pixel value of 0-256, and the ordinate is: the number of occurrences of each pixel value in the axial maximum intensity projection map;
Step S8, histogram prescribing is carried out on the axial maximum intensity projection histogram, a prescribing histogram is obtained, and probability distribution of each pixel value of the prescribing histogram and the template histogram is consistent; wherein, the template histogram refers to: processing the healthy oral cavity tooth area without implant teeth and without missing teeth in a mode of step S1-step S7 to generate an axial maximum intensity projection histogram;
step S9, gamma conversion is carried out on the specified histogram, and a picture after gamma conversion is obtained;
step S10, performing region growth on the image after gamma conversion to obtain a new binary image;
Step S11, carrying out two-dimensional connected domain analysis on the new binary image generated in the step S10, and extracting the connected domain with the largest pixel number as a dental arch region;
step S12, performing morphological closing operation on the dental arch region obtained in the step S11, and filling holes to obtain a dental arch region filled with the holes;
Step S13, carrying out axial transformation on the dental arch region filled with the holes obtained in the step S12 to generate dental archwires, and carrying out deburring operation on the generated dental archwires to generate dental archwires after deburring;
and S14, performing equal arc length sampling on the dental archwire subjected to the deburring generated in the step S13, and performing fitting of a cubic spline curve on the generated sampling points so as to extract a final dental archwire.
Preferably, in step S2, the following method is used to obtain a coronal maximum intensity projection map:
Setting each coronal CT slice in the coronal CT slice sequence to comprise n1 x m1 pixel points; wherein n1 is the number of rows and m1 is the number of columns;
one ray irradiates through 1*1 th pixel points of each coronal CT slice in the coronal CT slice sequence, and extracts the pixel value with the maximum gray value from all 1*1 th pixel points passing through the pixel points as the pixel value of the 1*1 th pixel point of the generated coronal maximum intensity projection graph;
One ray irradiates through 1*2 th pixel points of each coronal CT slice in the coronal CT slice sequence, and extracts the pixel value with the maximum gray value from all 1*2 th pixel points passing through the pixel points as the pixel value of the 1*2 th pixel point of the generated coronal maximum intensity projection graph;
And so on
One ray irradiates through the n1 x m1 pixel point of each coronal CT slice in the coronal CT slice sequence, and extracts the pixel value with the maximum gray value from the n1 x m1 pixel points which pass through, and the pixel value is used as the pixel value of the n1 x m1 pixel point of the generated coronal maximum intensity projection graph;
a coronal maximum intensity projection is thus obtained.
Preferably, in step S8, the histogram specification is performed using the following formula:
G(zq)＝sk
zq＝G(zq)-1
wherein:
g (z q) is the probability value of the axial maximum intensity projection histogram obtained in the step S7 in the range of 0-q pixel values;
L represents the number of levels of pixels, 256;
p z(zi) is the probability density function of the pixel value i of the axial maximum intensity projection histogram obtained in step S7;
s k is the probability value of the template histogram in the range of 0-k pixel values;
p z(zj) is a probability density function of the pixel value j of the template histogram;
G (z q)-1 represents an inversion operation on G (z q) to calculate a specified pixel value z q.
Preferably, in step S9, the following formula is used for gamma conversion:
s＝crγ
wherein:
s is the gamma-transformed image pixel value;
c is a positive constant;
Gamma is the intensity factor of the gamma transformation;
r is the image pixel value before gamma conversion.
The automatic extraction method of the dental archwire provided by the invention has the following advantages:
the whole dental arch line extraction process is automatically carried out, and the specification of the histogram is carried out by using templates in the middle process, so that the parameters used in the process of regional growth, morphological operation and gamma transformation have strong universality. Therefore, the whole method for extracting the dental arch line has strong real-time performance, high robustness and high accuracy and is fully and automatically carried out.
Drawings
Fig. 1 is a schematic flow chart of an automatic extraction method of dental archwire provided by the invention.
Detailed Description
In order to make the technical problems, technical schemes and beneficial effects solved by the invention more clear, the invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The invention provides an automatic extraction method of dental archwires, which replaces the existing process of manually selecting connection points in an oral dental arch area by a dentist, thereby improving the efficiency of planning a planting path before operation, improving the accuracy of dental archwire extraction, reducing the requirement on the experience of the dentist, and the whole method has the advantages of simple implementation, strong instantaneity, high robustness, high extraction precision and the like.
Referring to fig. 1, the present invention provides an automatic extraction method of dental archwire, comprising the steps of:
step S1, respectively performing crown CT scanning and axial CT scanning on a tooth area of a head to respectively obtain a crown CT slice sequence and an axial CT slice sequence; wherein, the coronal direction refers to: from hindbrain scoop to face direction, namely: from the back to the front; the axial direction refers to the top-down direction;
coronal CT slice sequences refer to: each coronal CT slice is overlapped along the front-back direction; each coronal CT slice is a vertical slice;
Axial CT slice sequences refer to: each axial CT slice is overlapped along the up-down direction; each axial CT slice is a horizontal slice;
step S2, carrying out crown maximum intensity projection on the crown CT slice sequence to obtain a crown maximum intensity projection diagram; the crown maximum intensity projection graph is a two-dimensional plane graph;
The crown maximum intensity projection map is obtained by adopting the following method:
Setting each coronal CT slice in the coronal CT slice sequence to comprise n1 x m1 pixel points; wherein n1 is the number of rows and m1 is the number of columns;
one ray irradiates through 1*1 th pixel points of each coronal CT slice in the coronal CT slice sequence, and extracts the pixel value with the maximum gray value from all 1*1 th pixel points passing through the pixel points as the pixel value of the 1*1 th pixel point of the generated coronal maximum intensity projection graph;
One ray irradiates through 1*2 th pixel points of each coronal CT slice in the coronal CT slice sequence, and extracts the pixel value with the maximum gray value from all 1*2 th pixel points passing through the pixel points as the pixel value of the 1*2 th pixel point of the generated coronal maximum intensity projection graph;
And so on
One ray irradiates through the n1 x m1 pixel point of each coronal CT slice in the coronal CT slice sequence, and extracts the pixel value with the maximum gray value from the n1 x m1 pixel points which pass through, and the pixel value is used as the pixel value of the n1 x m1 pixel point of the generated coronal maximum intensity projection graph;
a coronal maximum intensity projection is thus obtained.
Step S3, counting pixels of the crown maximum intensity projection graph to generate a crown maximum intensity projection histogram; wherein, the abscissa of the coronal maximum intensity projection histogram is a pixel value of 0-256, and the ordinate is: the number of occurrences of each pixel value in the coronal maximum intensity projection map;
Fitting normal distribution to the crown maximum intensity projection histogram to obtain a mean mu 0 and a variance sigma 0 after normal distribution fitting; from the mean μ 0 and the variance σ 0, the binarization threshold threshHold is obtained using the following formula:
threshHold＝μ0+kσ0
Wherein: k is an empirical coefficient, preferably a value of 1.98;
When the coronary maximum intensity projection graph is binarized, the binarization threshold value calculated by the method provided by the invention can maximize the inter-class variance of the pixel values of all the pixel points in the coronary maximum intensity projection graph, so that background pixels and foreground pixels can be effectively distinguished, and the binarization accuracy is improved.
Step S4, binarizing the crown maximum intensity projection image generated in the step S2 by using the binarization threshold threshHold generated in the step S3, so as to generate a crown binarized image;
The binarization method comprises the following steps: for each pixel point in the coronal maximum intensity projection graph, if the pixel value is less than a binarization threshold threshHold, changing the pixel value to 0; otherwise, the pixel value is changed to 1;
S5, the image coordinate system of the coronal binarized image is a u-v coordinate system; wherein the v axis is in the vertical direction; the u-axis is the direction perpendicular to the v-axis in the image;
And carrying out statistics on the number of pixels along the v axis of the coronal binarized image, namely: drawing a straight line L1 parallel to a u axis at a v=1 position in the coronal binarized image, and counting the number N1 of pixel points, with the pixel value of 1, of the coronal binarized image, through which the straight line L1 passes; drawing a straight line L2 parallel to the u axis at the position of v=2, and counting the number N2 of pixel points with the pixel value of 1 of the coronal binarized image through which the straight line L2 passes; according to the classification, counting the number of pixels in the v-axis direction of the coronal binarized image is completed, and a plurality of discrete points in a coordinate system with the abscissa being the v-axis and the ordinate being the number N of pixel points are obtained; fitting the normal distribution of each obtained discrete point to obtain a mean mu 1 and a variance sigma 1 after fitting the normal distribution;
according to the mean mu 1 and the variance sigma 1 after normal distribution fitting, the following formula is adopted to obtain a CT slice starting position downSlice entering the axial maximum intensity projection and a CT slice ending position upSlice entering the axial maximum intensity projection:
upSlice＝μ1+kuσ1
downSlice＝μ1-kdσ1
wherein:
k u and k d are empirical coefficients, preferably a value of 2.56;
S6, selecting all axial CT slices with slice numbers of downSlice-upSlice from top to bottom in the axial CT slice sequence obtained in the step S1 to form an axial CT slice sequence set;
performing axial maximum intensity projection on the axial CT slice sequence set to obtain an axial maximum intensity projection diagram;
therefore, in the invention, only the axial CT slices which are selected in the range downSlice-upSlice are subjected to axial maximum intensity projection, but not all the axial CT slices are subjected to axial maximum intensity projection, and the processing mode has the advantages that: the axial CT slice which is selected by the invention and is in the range of downSlice-upSlice is a tooth area, and the interference area is obviously removed, so that the complexity of the subsequent dental arch wire extraction can be reduced, and the precision of the subsequent dental arch wire automatic extraction can be improved.
S7, counting pixels of the axial maximum intensity projection graph to generate an axial maximum intensity projection histogram; wherein, the abscissa of the axial maximum intensity projection histogram is a pixel value of 0-256, and the ordinate is: the number of occurrences of each pixel value in the axial maximum intensity projection map;
Step S8, histogram prescribing is carried out on the axial maximum intensity projection histogram, a prescribing histogram is obtained, and probability distribution of each pixel value of the prescribing histogram and the template histogram is consistent; wherein, the template histogram refers to: processing the healthy oral cavity tooth area without implant teeth and without missing teeth in a mode of step S1-step S7 to generate an axial maximum intensity projection histogram;
In this step, histogram specification is performed using the following formula:
G(zq)＝sk
zq＝G(zq)-1
wherein:
g (z q) is the probability value of the axial maximum intensity projection histogram obtained in the step S7 in the range of 0-q pixel values;
L represents the number of levels of pixels, 256;
p z(zi) is the probability density function of the pixel value i of the axial maximum intensity projection histogram obtained in step S7;
s k is the probability value of the template histogram in the range of 0-k pixel values;
p z(zj) is a probability density function of the pixel value j of the template histogram;
G (z q)-1 represents an inversion operation on G (z q) to calculate a specified pixel value z q.
Step S9, gamma conversion is carried out on the specified histogram, and a picture after gamma conversion is obtained;
in this step, the following formula is used for gamma conversion:
S＝crγ
wherein:
s is the gamma-transformed image pixel value;
c is a positive constant, preferably 1;
Gamma is the intensity factor of the gamma transformation;
r is the image pixel value before gamma conversion.
Step S10, performing region growth on the image after gamma conversion to obtain a new binary image;
Step S11, carrying out two-dimensional connected domain analysis on the new binary image generated in the step S10, and extracting the connected domain with the largest pixel number as a dental arch region;
step S12, performing morphological closing operation on the dental arch region obtained in the step S11, and filling holes to obtain a dental arch region filled with the holes;
Step S13, carrying out axial transformation on the dental arch region filled with the holes obtained in the step S12 to generate dental archwires, and carrying out deburring operation on the generated dental archwires to generate dental archwires after deburring;
and S14, performing equal arc length sampling on the dental archwire subjected to the deburring generated in the step S13, and performing fitting of a cubic spline curve on the generated sampling points so as to extract a final dental archwire.
According to the automatic extraction method of the dental arch wire, the whole dental arch wire extraction process is automatically carried out, and the specification of the histogram is carried out by using the template in the middle process, so that the parameters used in the process of regional growth, morphological operation and gamma transformation have strong universality. Therefore, the whole method for extracting the dental arch line has strong real-time performance, high robustness and high accuracy and is fully and automatically carried out.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which is also intended to be covered by the present invention.
Claims (4)
1. An automatic dental arch wire extraction method is characterized by comprising the following steps:
step S1, respectively performing crown CT scanning and axial CT scanning on a tooth area of a head to respectively obtain a crown CT slice sequence and an axial CT slice sequence; wherein, the coronal direction refers to: from hindbrain scoop to face direction, namely: from the back to the front; the axial direction refers to the top-down direction;
coronal CT slice sequences refer to: each coronal CT slice is overlapped along the front-back direction; each coronal CT slice is a vertical slice;
Axial CT slice sequences refer to: each axial CT slice is overlapped along the up-down direction; each axial CT slice is a horizontal slice;
step S2, carrying out crown maximum intensity projection on the crown CT slice sequence to obtain a crown maximum intensity projection diagram; the crown maximum intensity projection graph is a two-dimensional plane graph;
Step S3, counting pixels of the crown maximum intensity projection graph to generate a crown maximum intensity projection histogram; wherein, the abscissa of the coronal maximum intensity projection histogram is a pixel value of 0-256, and the ordinate is: the number of occurrences of each pixel value in the coronal maximum intensity projection map;
Fitting normal distribution to the crown maximum intensity projection histogram to obtain a mean mu 0 and a variance sigma 0 after normal distribution fitting; from the mean μ 0 and the variance σ 0, the binarization threshold threshHold is obtained using the following formula:
threshHold＝μ0+kσ0
wherein: k is an empirical coefficient;
step S4, binarizing the crown maximum intensity projection image generated in the step S2 by using the binarization threshold threshHold generated in the step S3, so as to generate a crown binarized image;
The binarization method comprises the following steps: for each pixel point in the coronal maximum intensity projection graph, if the pixel value is less than a binarization threshold threshHold, changing the pixel value to 0; otherwise, the pixel value is changed to 1;
S5, the image coordinate system of the coronal binarized image is a u-v coordinate system; wherein the v axis is in the vertical direction; the u-axis is the direction perpendicular to the v-axis in the image;
And carrying out statistics on the number of pixels along the v axis of the coronal binarized image, namely: drawing a straight line L1 parallel to a u axis at a v=1 position in the coronal binarized image, and counting the number N1 of pixel points, with the pixel value of 1, of the coronal binarized image, through which the straight line L1 passes; drawing a straight line L2 parallel to the u axis at the position of v=2, and counting the number N2 of pixel points with the pixel value of 1 of the coronal binarized image through which the straight line L2 passes; according to the classification, counting the number of pixels in the v-axis direction of the coronal binarized image is completed, and a plurality of discrete points in a coordinate system with the abscissa being the v-axis and the ordinate being the number N of pixel points are obtained; fitting the normal distribution of each obtained discrete point to obtain a mean mu 1 and a variance sigma 1 after fitting the normal distribution;
according to the mean mu 1 and the variance sigma 1 after normal distribution fitting, the following formula is adopted to obtain a CT slice starting position downSlice entering the axial maximum intensity projection and a CT slice ending position upSlice entering the axial maximum intensity projection:
upSlice＝μ1+kuσ1
downSlice＝μ1-kdσ1
wherein:
k u and k d are both empirical coefficients;
S6, selecting all axial CT slices with slice numbers of downSlice-upSlice from top to bottom in the axial CT slice sequence obtained in the step S1 to form an axial CT slice sequence set;
performing axial maximum intensity projection on the axial CT slice sequence set to obtain an axial maximum intensity projection diagram;
S7, counting pixels of the axial maximum intensity projection graph to generate an axial maximum intensity projection histogram; wherein, the abscissa of the axial maximum intensity projection histogram is a pixel value of 0-256, and the ordinate is: the number of occurrences of each pixel value in the axial maximum intensity projection map;
Step S8, histogram prescribing is carried out on the axial maximum intensity projection histogram, a prescribing histogram is obtained, and probability distribution of each pixel value of the prescribing histogram and the template histogram is consistent; wherein, the template histogram refers to: processing the healthy oral cavity tooth area without implant teeth and without missing teeth in a mode of step S1-step S7 to generate an axial maximum intensity projection histogram;
step S9, gamma conversion is carried out on the specified histogram, and a picture after gamma conversion is obtained;
step S10, performing region growth on the image after gamma conversion to obtain a new binary image;
Step S11, carrying out two-dimensional connected domain analysis on the new binary image generated in the step S10, and extracting the connected domain with the largest pixel number as a dental arch region;
step S12, performing morphological closing operation on the dental arch region obtained in the step S11, and filling holes to obtain a dental arch region filled with the holes;
Step S13, carrying out axial transformation on the dental arch region filled with the holes obtained in the step S12 to generate dental archwires, and carrying out deburring operation on the generated dental archwires to generate dental archwires after deburring;
and S14, performing equal arc length sampling on the dental archwire subjected to the deburring generated in the step S13, and performing fitting of a cubic spline curve on the generated sampling points so as to extract a final dental archwire.
2. The automatic extraction method of dental archwire according to claim 1, wherein in step S2, a crown maximum intensity projection is obtained by using the following method:
Setting each coronal CT slice in the coronal CT slice sequence to comprise n1 x m1 pixel points; wherein n1 is the number of rows and m1 is the number of columns;
one ray irradiates through 1*1 th pixel points of each coronal CT slice in the coronal CT slice sequence, and extracts the pixel value with the maximum gray value from all 1*1 th pixel points passing through the pixel points as the pixel value of the 1*1 th pixel point of the generated coronal maximum intensity projection graph;
One ray irradiates through 1*2 th pixel points of each coronal CT slice in the coronal CT slice sequence, and extracts the pixel value with the maximum gray value from all 1*2 th pixel points passing through the pixel points as the pixel value of the 1*2 th pixel point of the generated coronal maximum intensity projection graph;
And so on
One ray irradiates through the n1 x m1 pixel point of each coronal CT slice in the coronal CT slice sequence, and extracts the pixel value with the maximum gray value from the n1 x m1 pixel points which pass through, and the pixel value is used as the pixel value of the n1 x m1 pixel point of the generated coronal maximum intensity projection graph;
a coronal maximum intensity projection is thus obtained.
3. The automatic dental archwire extraction method according to claim 1, wherein in step S8, histogram specification is performed using the following formula:
G(zq)＝sk
zq＝G(zq)-1
wherein:
g (z q) is the probability value of the axial maximum intensity projection histogram obtained in the step S7 in the range of 0-q pixel values;
L represents the number of levels of pixels, 256;
p z(zi) is the probability density function of the pixel value i of the axial maximum intensity projection histogram obtained in step S7;
s k is the probability value of the template histogram in the range of 0-k pixel values;
p z(zj) is a probability density function of the pixel value j of the template histogram;
G (z q)-1 represents an inversion operation on G (z q) to calculate a specified pixel value z q.
4. The automatic dental archwire extraction method of claim 1, wherein in step S9, the gamma transformation is performed using the following formula:
s＝crγ
wherein:
s is the gamma-transformed image pixel value;
c is a positive constant;
Gamma is the intensity factor of the gamma transformation;
r is the image pixel value before gamma conversion.
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