KR20210015208A - Method of providing the information for predicting the effect of tooth whitening - Google Patents

Abstract

The present invention relates to a method of providing information to quantitatively predict the effect of tooth whitening and, more specifically, to a method of providing information to predict the effect of tooth whitening, which includes the step of taking at least one of a white photograph and a fluorescence photograph of a tooth using quantitative light-induced fluorescence (QLF).

Description

Method of providing the information for predicting the effect of tooth whitening

The present invention relates to a method for providing information for predicting the whitening effect of teeth.

The teeth are composed of two layers, enamel and dentin, and food pigments enter the micropores formed in the enamel over a long period of time, causing the teeth to become yellow. Discoloration caused by food is mostly improved by brushing teeth and scaling, but whitening the discoloration of teeth that cannot be resolved in this way is called teeth whitening, and usually, the whitening agent penetrates into the teeth and decomposes pigments. .

In general, hydrogen peroxide is used as a whitening agent. Hydrogen peroxide releases oxygen free groups or perhydroxyl free groups, and then the released free groups (radicals) are very unstable, have electron affinity, and bind with other organic molecules to obtain stability while continuously generating free groups. As a result, teeth whitening proceeds. Looking more at the reaction, hydrogen peroxide increases the osmoticity of the hemorrhoids, allowing ions to move easily within the hemorrhoids, thereby decomposing them into water and carbon dioxide by an oxidation-reduction reaction to molecules representing organic components and pigments in the hard tissue. Will go through.

Traditionally, clinicians have applied tooth tint to a shade guide to predict a patient's teeth whitening effect. However, even if the color tone is the same, the whitening reaction may appear differently depending on patient characteristics, tooth structure, and components. Nevertheless, until now, prediction models for tooth whitening have only been developed using only tooth tone. Therefore, research and development of a method that can more accurately predict the teeth whitening effect is required.

An object of the present invention is to provide an information providing method for predicting the whitening effect of teeth using a quantitative light-induced fluorescence digital (QLF-D) method.

Another object of the present invention is to provide an information providing device for predicting the whitening effect of teeth using a quantitative light-induced fluorescence-digital device (QLF-D).

Other objects and advantages of the present invention will become more apparent by the following detailed description, claims and drawings.

According to an embodiment of the present invention, predicting a tooth whitening effect, comprising taking at least one of a white photo and a fluorescence photo of a tooth using quantitative light-induced fluorescence (QLF) It relates to a method of providing information to

In the present invention, the "quantitative light-induced fluorescence (QLF)" is a digital camera to detect autofluorescence expressed by a fluorophore in the tooth by irradiating a light source of 405 nm. As an optical technology to visualize through, in the present invention, teeth can be photographed with a QLF device including both a white light and/or fluorescent light source (eg, LED), preferably a white light and fluorescent light source.

The present invention can predict the whitening effect in various teeth of central incisors (incisors), lateral incisors (incisors), canines (canines), premolars (small molars), or molars (large molars), but is not limited thereto.

In the present invention, one or all portions of the tooth may be photographed with QLF, and the photographing region is not particularly limited.

In the present invention, the QLF may be photographed before, during, or after the whitening treatment on the teeth, but preferably, the QLF may be photographed before the teeth whitening treatment.

In the present invention, by photographing a tooth with a QLF as described above, at least one of a white photo and a fluorescence photo, preferably a fluorescence photo, more preferably a white photo and a fluorescence photo can be obtained.

In the present invention, in order to predict the tooth whitening effect, at least one of an L* value, a* value, and b* value may be measured from the obtained white photo. Hereinafter, the L* value obtained from the white photo is'WL*' , The a* value obtained from the white photo is represented by'Wa*', and the b* value obtained from the white photo is represented by "Wb*".

In addition, in the present invention, in order to predict the tooth whitening effect, at least one of an L* value, a* value, and b* value may be measured from the obtained fluorescence image. Hereinafter, the L* value obtained from the fluorescence image is'FL *', the a* value obtained from the fluorescence picture is expressed as'Fa*', and the b* value obtained from the fluorescence picture is expressed as'Fb*'.

In the present invention, the L*, a* and b* values are based on the CIE L*, a*, b* models proposed by the Commission International d'Eclairge (CIE), and the L* is the luminous intensity ( Brightness) element, and a* and b* represent hue elements representing a range from green (-a*) to red (+a*) and blue (-b*) to yellow (+b*), respectively.

In addition, in the present invention, each of the WL*, Wa*, and Wb* values may be values measured at any one spot in the white photo, or may be an average value of values measured at a plurality of spots, It is not limited thereto. Here, in the case of an average value of values measured in the plurality of spots, some areas of the plurality of spots may or may not overlap.

In addition, in the present invention, each of the FL*, Fa*, and Fb* values may be a value measured at any one spot in the fluorescent photograph, or may be an average value of values measured at a plurality of spots, but is limited thereto. It is not. Here, in the case of an average value of values measured in the plurality of spots, some areas of the plurality of spots may or may not overlap.

In addition, in the present invention, each of the WL*, Wa* and Wb* values may be an average value of values measured at arbitrary spots of a plurality of teeth among white photographs of a plurality of teeth, or at a plurality of spots of a plurality of teeth. It may be an average value of the measured values, but is not limited thereto.

In addition, in the present invention, each of the FL*, Fa*, and Fb* values may be an average value of a value measured at an arbitrary spot of a plurality of teeth among white photographs of a plurality of teeth, or at a plurality of spots of a plurality of teeth. It may be an average value of the measured values, but is not limited thereto.

In the present invention, the shape or size of any spot for measuring the WL*, Wa*, Wb*, FL*, Fa* and Fb* values is not particularly limited, but, for example, the diameter is 0.1 to 10 cm, preferably Preferably, it may be a circular shape having a diameter of 0.5 to 5 cm, more preferably 1 cm in diameter.

In an example of the present invention, in order to predict the tooth whitening effect, the measured WL*, Wa*, Wb*, FL*, Fa* and Fb* values are substituted into Equation 1 below to obtain a total color difference of ΔE*. Can measure:

[Equation 1]

△E*= (A×WL* + B×Wa* + C×Wb*)-(D×FL* + E×Fa* + F×Fb*) + G

In Equation 1 above,

The A may be a rational number of -0.38 to -0.18, preferably a rational number of -0.30 to -0.24, more preferably a rational number of -0.28 to -0.26, most preferably -0.274 days I can.

B may be a rational number of 0.52 to 0.72, preferably may be a rational number of 0.59 to 0.65, more preferably a rational number of 0.61 to 0.62, and most preferably may be 0.615.

The C may be a rational number of 0.82 to 1.2, preferably 0.89 to 0.94, more preferably 0.91 to 0.92, and most preferably 0.916.

The D may be a rational number of 0.22 to 0.42, preferably a rational number of 0.29 to 0.35, more preferably a rational number of 0.31 to 0.32, and most preferably 0.316.

E may be a rational number of 0.85 to 0.95, preferably 0.83 to 0.88, more preferably 0.85 to 0.86 rational number, most preferably 0.852.

The F may be a rational number of 0.10 to 0.30, preferably 0.17 to 0.23, more preferably 0.19 to 0.20 rational number, and most preferably 0.195.

The G may be a rational number of 15 to 20, preferably a rational number of 17.44 to 19.44, more preferably a rational number of 18.4 to 18.5, and most preferably may be 18.44.

In the present invention, the larger the ΔE* value, which is the total color difference obtained from Equation 1, the more effective the tooth whitening will be, that is, it can be predicted that the whitening efficiency will be high when the tooth is whitened, and preferably the ΔE* value is 2 Above, in the case of 2.0 to 3.7 or more, it can be predicted that the tooth whitening efficiency will be excellent.

In another example of the present invention, in order to predict the tooth whitening effect, when the measured value of WL* is 52 to 53 or less, preferably 52.8 or less, and Wb* is 8 to 9 or less, preferably 8.8 or less, It can be predicted that the whitening efficiency will be high when the tooth is whitened.

In another example of the present invention, in order to predict the tooth whitening effect, the measured value of WL* is 52 to 53 or less, preferably 52.8 or less, and Wb* is greater than 8 to 9, preferably greater than 8.8. In this case, it can be predicted that the whitening efficiency will be moderate when the tooth is whitened.

In another example of the present invention, in order to predict the tooth whitening effect, the measured value of WL* is greater than 52 to 53, preferably greater than 52.8, and the Fb* is greater than 10 to 11, preferably greater than 10.5. In this case, it can be predicted that the whitening efficiency will be low when the tooth is whitened.

In another example of the present invention, in order to predict the tooth whitening effect, the measured value of WL* is greater than 52 to 53, preferably greater than 52.8, and Fb* is 10 to 11 or less, preferably 10.5 or less. , It can be predicted that the whitening efficiency will be moderate when the tooth is whitened.

11 is a diagram showing a prediction criterion for a tooth whitening effect according to an embodiment of the present invention. Specifically, the value of (1) WL* measured at an arbitrary spot of a white photo taken of a desired part of a tooth taken by QLF is 52.8 or less, and a Wb* measured at an arbitrary spot of the white photo is 8.8 or less. In this case, it can be predicted that the tooth whitening efficiency will be high, and (2) the value of WL* is greater than 52.8, and the Fb* is greater than 10.5 at any spot in the fluorescence photograph taken of the desired part of the tooth taken with QLF. , It can be predicted that the tooth whitening efficiency will be low.

According to another embodiment of the present invention, a photographing unit for photographing at least one of a white photo and a fluorescence photo of a tooth using quantitative light-induced fluorescence (QLF);

An input unit for inputting a color tone value measured from at least one of a white photo and a fluorescence photo of the tooth obtained by the photographing unit; And

It relates to an information providing apparatus for predicting the effect of whitening teeth, including a calculation unit for predicting the whitening effect of the teeth from the color tone value obtained by the input unit.

In the present invention, the photographing unit may include a digital camera capable of photographing self-fluorescence of teeth using quantitative light-induced fluorescence, and a light source of white light and/or fluorescence, preferably a light source of white light and fluorescence Can contain all.

In the present invention, at least one of a white photograph and a fluorescent photograph, preferably a fluorescent photograph, more preferably a white photograph and a fluorescent photograph, may be obtained by photographing the teeth with the QLF by the photographing unit as described above.

In the present invention, in the input unit, a color tone value may be measured and input from at least one of a white photo and a fluorescent photo obtained by the photographing unit, and preferably, among WL* values, Wa* values, and Wb* values obtained from the white photo At least one may be measured and input, or at least one of a FL* value, a Fa* value, and an Fb* value obtained from the fluorescence photograph may be measured and input.

In the present invention, the operation unit may predict the effect of tooth whitening by using at least one of WL*, Wa*, Wb*, FL*, Fa*, and Fb* values input from the input unit.

In one example of the present invention, in the calculation unit, the WL*, Wa*, Wb*, FL*, Fa*, and Fb* values input from the input unit are substituted into Equation 1 below to measure the total color difference ΔE*. Can be:

[Equation 1]

△E*= (A×WL* + B×Wa* + C×Wb*)-(D×FL* + E×Fa* + F×Fb*) + G

In Equation 1 above,

The A may be a rational number of -0.38 to -0.18, preferably a rational number of -0.30 to -0.24, more preferably a rational number of -0.28 to -0.26, most preferably -0.274 days I can.

B may be a rational number of 0.52 to 0.72, preferably may be a rational number of 0.59 to 0.65, more preferably a rational number of 0.61 to 0.62, and most preferably may be 0.615.

The C may be a rational number of 0.82 to 1.2, preferably 0.89 to 0.94, more preferably 0.91 to 0.92, and most preferably 0.916.

The D may be a rational number of 0.22 to 0.42, preferably a rational number of 0.29 to 0.35, more preferably a rational number of 0.31 to 0.32, and most preferably 0.316.

E may be a rational number of 0.85 to 0.95, preferably 0.83 to 0.88, more preferably 0.85 to 0.86 rational number, most preferably 0.852.

The F may be a rational number of 0.10 to 0.30, preferably 0.17 to 0.23, more preferably 0.19 to 0.20 rational number, and most preferably 0.195.

The G may be a rational number of 15 to 20, preferably a rational number of 17.44 to 19.44, more preferably a rational number of 18.4 to 18.5, and most preferably may be 18.44.

In the calculation unit of the present invention, as the value of ΔE*, which is the total color difference obtained from Equation 1, increases, it can be predicted that the tooth whitening will be effective, that is, the tooth whitening efficiency will be high. To 3.7 or more, it can be predicted that the tooth whitening efficiency will be excellent.

In another example of the present invention, in the operation unit, when the value of WL* input from the input unit is 52 to 53 or less, preferably 52.8 or less, and the Wb* is 8 to 9 or less, preferably 8.8 or less, the corresponding tooth It can be predicted that the whitening efficiency will be high during the whitening treatment.

In another example of the present invention, in the calculation unit, when the value of WL* input from the input unit is 52 to 53 or less, preferably 52.8 or less, and Wb* is greater than 8 to 9, preferably greater than 8.8, It can be predicted that the whitening efficiency will be moderate when the tooth is whitened.

In another example of the present invention, in the calculation unit, when the value of WL* input from the input unit is 52 to 53 or more, preferably 52.8 or more, and Fb* is 10 to 11 or more, preferably 10.5 or more, It can be predicted that the whitening efficiency will be low when the tooth is whitened.

In another example of the present invention, in the calculation unit, when the value of WL* input from the input unit is more than 52 to 53, preferably more than 52.8, and the Fb* is 10 to 11 or less, preferably 10.5 or less, It can be predicted that the whitening efficiency will be moderate when the teeth are whitened.

The apparatus of the present invention may further include a display unit for displaying a result predicted by the operation unit. In the present invention, the display unit may be configured as an output means such as a display and a speaker, but is not limited thereto.

The apparatus of the present invention may further include a memory for storing a program for the operation of the input unit or the operation unit, and temporarily storing input/output data. In the present invention, the memory may include a read only memory (ROM) and a random access memory (RAM).

In addition, the device of the present invention may further include storage including various types of volatile or nonvolatile storage media, such as the memory. The storage may be implemented as a web storage that performs a memory storage function on the Internet, but is not limited thereto.

In addition, the apparatus of the present invention may further include a network interface that enables wired/wireless communication with other terminals through a network. In the present invention, the network interface may use any one or more of communication technologies such as wireless Internet, mobile communication, and short-range communication, but is not limited thereto.

1 is a diagram showing an information providing device for predicting the effect of tooth whitening according to an embodiment of the present invention, a photographing unit 100, an input unit 110, an operation unit 120, a display unit 130, a memory ( 140), storage 150, and a network interface 160.

In the present invention, it is possible to quantitatively predict the degree of efficiency when the teeth are whitened relatively accurately and quickly using a quantitative light-induced fluorescence-digital method.

1 is a diagram showing an information providing device for predicting the effect of whitening teeth according to an embodiment of the present invention.
Figure 2 shows the results of taking a white photograph and a fluorescence photograph of the tooth buccal surface and tooth cross section of the tooth specimen in Example 1 of the present invention.
3 shows an example of setting a region to obtain a CIELAB value from a white photograph and a fluorescence photograph of a tooth specimen in Example 1 of the present invention.
FIG. 4 shows an example of setting a region for analyzing a tooth component by Raman spectroscopy for a tooth specimen subjected to tooth whitening in Example 1 of the present invention.
FIG. 5 shows a Raman graph showing the locations and strengths of the inorganic and organic peaks of a tooth with respect to a tooth specimen in Example 1 of the present invention.
6 is a graph showing a comparison of values by quantifying the intensity according to the vibration position of the molecule after Raman spectroscopy analysis of the tooth specimen in Example 1 of the present invention.
7 shows a photograph of analyzing changes in color tone, fluorescence, and composition of teeth after performing tooth whitening on a tooth specimen in Example 1 of the present invention.
8 shows the results of comparing Raman graphs before and after tooth whitening with respect to a tooth specimen in Example 1 of the present invention.
9 is a graph showing a correlation between ΔE*, which is a color tone change value in a white photograph of a tooth specimen in Example 1 of the present invention, and each color tone variable Lab before tooth whitening, in a linear regression equation.
10 is a graph showing a correlation between ΔE*, which is a color tone change value in a fluorescence photograph of a tooth specimen in Example 1 of the present invention, and each color tone variable Lab before tooth whitening, by a linear regression equation.
11 is a diagram showing a prediction criterion for a tooth whitening effect according to an embodiment of the present invention.

Hereinafter, the present invention will be described in more detail through examples. These examples are only for describing the present invention in more detail, and it will be apparent to those of ordinary skill in the art that the scope of the present invention is not limited by these examples according to the gist of the present invention. .

Example

[Example 1]

1. Preparation of the Psalms

A total of 61 specimens were obtained by cutting the extracted human teeth, and teeth whitening was performed by immersing in 35% hydrogen peroxide for 1 hour.

2. QLF-D shooting and CIELAB analysis

Before and after whitening of the tooth specimen, a white photograph and a fluorescence photograph of the specimen prepared in 1. were taken under the following conditions using a QLF-D with white light and fluorescent LED attached: a white photograph; SS 1/60s, AV 13.0, ISO 1600, fluorescence photography; SS 1/45s, AV 9.0, ISO 1600. Figure 2 shows the result of taking a white photograph and a fluorescence photograph of the tooth buccal surface and tooth cross section of a specimen before tooth whitening under the above conditions. Thereafter, each photo was loaded using an image J program, and as shown in FIG. 3, a desired part was set in a circular shape of 1 mm, and CIELAB values were obtained.

3. Analysis of tooth composition

Using Raman spectrometry, the components of the teeth were analyzed in the area shown in FIG. 4 with respect to the specimen before tooth whitening prepared in 1. above. Through the Raman graph obtained as shown in FIG. 5, the positions and intensity of the inorganic and organic peaks of the tooth could be confirmed. In addition, the intensity according to the vibration position of the molecule can be numerically compared and values can be compared. In particular, FWHM indicating crystallinity and FI value, which is Raman fluorescence data, were obtained in the vibration part 1 showing the highest intensity. The results are as shown in Fig. 6, where RRI (Raman relative intensity) represents inorganic information, and FI (fluorescence intensity) is a distinct fluorescence characteristic that appears in Raman when measuring enamel, meaning an inorganic-organic interface. It means a part in which inorganic and organic substances are chemically connected. In addition, in the graph of FIG. 6, an increase in the full width of half maximum (FWHM), that is, a decrease in the width indicates an increase in crystallinity.

4. Correlation analysis between CIELAB value and Raman component analysis

The CIELAB numerical values obtained from white photographs and fluorescence photographs for the specimens before tooth whitening in the above 2 were compared with the Raman component analysis results obtained in 3, and the results are shown in Table 1 below.

Correlation between Raman intensity and CIELAB values on the enamel surface _V1 PO4 ^3- _V2 PO4 ^3- _V4 PO4 ^3- CO ₃ FWHM FI White photo L* -0.094 -0.168 -0.113 -0.023 0.131 -0.084 a* -0.030 0.055 0.105 -0.115 -0.051 0.246 b* 0.002 0.248 0.268* 0.052 -0.166 0.350** Fluorescence photo L* 0.101 0.150 -0.053 -0.031 -0.271* 0.042 a* -0.042 0.057 0.198 -0.073 -0.057 0.275* b* 0.087 0.293* 0.228 -0.134 -0.433*** 0.450*** Pearson correlation coefficient, P<0.05*, P<0.001**, P<0.001***

As shown in Table 1, a number of variables having a statistically significant relationship with tooth components in fluorescence rather than white light hue in enamel were identified. In particular, the yellowness (b*) of the tooth in the fluorescence photograph is FWHM (r=-0.433, p<0.001), which represents the crystallinity of enamel, and FI (r=0.450, p<0.001), which represents the value of the inorganic-organic interface. There was a moderate relationship to and. Therefore, in actual clinical practice, the composition, crystallinity, and inorganic-organic interface of enamel can be inferred through QLF-D fluorescence images of teeth, and the tooth whitening effect can be predicted using this.

5. Changes before and after teeth whitening

After tooth whitening was performed by immersing the teeth in hydrogen peroxide in the above 1., changes in color tone, fluorescence, and composition of the teeth were checked, compared and analyzed. As a result, as shown in FIG. 7, it was observed that the natural fluorescence became dark with the change of the color tone brightening after tooth whitening, and it was confirmed that the composition of the tooth also changed. In addition, Raman graphs before and after tooth whitening on the enamel surface were compared, and the results are shown in FIG. 8. Through the ratio calculation (RRI/FI), it was confirmed that the FI, that is, the inorganic-organic interface, was particularly reduced rather than the inorganic change after tooth whitening compared to before tooth whitening. In addition, it was confirmed that the fluorophore was oxidized after tooth whitening through QLF fluorescence and Raman analysis. In addition, in each of the white photographs and fluorescence photographs, the correlation between ΔRRI/FI and ΔL*, Δa*, and Δb* values after tooth whitening was analyzed, and the results are shown in Table 2 below.

Correlation between △RRI/FI and △L*, △a*, △b* values after tooth whitening White photo Fluorescence photo r p-value r p-value △L* -0.113 0.362 0.207 0.093 △a* -0.249 0.042 -0.279 0.022 △b* 0.098 0.429 -0.330 0.006 r: Pearson correlation coefficient

As shown in Table 2 above, in the correlation analysis result of the amount of change before and after tooth whitening, the change in the fluorescence photo was more related to the whitening of the tooth than the change in the white photo, and the change in fluorescence according to the component change after the tooth whitening treatment As a result, it was confirmed that the fluorescence variable was a variable related to tooth whitening, and thus it was applicable to the prediction model of the whitening effect.

6. Formula setting for deriving △E* from white photo and fluorescence photo

In order to develop a predictive model of the tooth whitening effect, a new equation for deriving the ΔE* value in the white photograph and fluorescence photograph of the buccal surface of the specimen obtained in 2 above was developed, which is shown in Equation 2 below:

[Equation 2]

△E*= -0.274×WL* +0.615×Wa* +0.916×Wb* -0.316×FL* -0.852×Fa* -0.195×Fb* +18.440

7. Formula setting to derive △E* from white photo

In order to compare the accuracy of prediction of the tooth whitening effect of Equation 2 using both a white photograph and a fluorescent photograph, Equation 3 for deriving the ΔE* value using only a white photograph as a comparative example is as follows:

[Equation 3]

△E*= -0.278×WL* +0.253×Wa* +0.569×Wb* + 21.700

8. Accuracy of prediction of tooth whitening effect

The correlation between the ΔE* values obtained in 6. and 7 above and the actual tooth whitening effect was analyzed, and the results are shown in Table 3 below.

R R ² F p-value △E* in Equation 2 0.607 0.368 6.020 <0.001 △E* in Equation 3 0.508 0.258 7.550 <0.001 R: Pearson correlation coefficient; R ² : coefficient of determination

As shown in Table 3, the △E* value obtained from Equation 2 based on the CIELAB value obtained from the white photograph and the fluorescence photograph was compared to the △E* value obtained from Equation 3 based on the CIELAB value obtained using only the white photograph. It could be seen that the correlation coefficient (R) and the determination coefficient (R ² ) increased by 11%, that is, showed a remarkably high correlation with the actual whitening effect.

9. Prediction of teeth whitening effect using only white photo or fluorescence photo

The correlation between ΔE*, which is a color tone change value in each of a white photo or a fluorescent photo, and each color tone variable (Lab) before tooth whitening is shown in FIGS. 9 and 10 by a linear regression equation. In the white photo of FIG. 9, the linear regression equation between ΔE* and each color tone variable before tooth whitening is as follows, and is also shown at the top of each drawing: WL* value (ΔE*= -0.277×L* + 26.091), Wa* value (ΔE*=0.093×a*+12.025), Wb* value (ΔE*=0.610×b*+7.444). In addition, the linear regression equation between ΔE* and each color tone variable before tooth whitening in the fluorescence photograph of FIG. 10 is as follows, and is also shown at the top of each figure: FL* (△E*= -0.060×L* + 14.205), Fa* (ΔE*= -0.049×a*+14.205), Fb* (ΔE*= -0.098×b*+13.021).

As a result, among the hue variables (WL, Wa, Wb) of the white photo of FIG. 9, WL and Wb showed a significant linear relationship as r= -0.373 (p=0.001) and r=0.353 (p=0.001), respectively. However, the color tone variables (FL, Fa, Fb) of the fluorescence photograph of FIG. 10 did not show a significant correlation. Nevertheless, as shown in Table 3, the multiple regression model combining the white photo and the fluorescence photo improved the explanatory power of the tooth whitening effect by 11% in the model using the fluorescent photo together than the model predicted with only white photo.

10. Establishment of predictive classification system for tooth whitening effect

In order to predict the tooth whitening effect in actual clinical trials using the CIELAB value obtained in 2 above, a predictive taxonomy of the tooth whitening effect of FIG. 11 was set based on the decision tree analysis.

11. Conclusion

Through the above experiment, autofluorescence may be expressed differently depending on the composition of the tooth, and it was found that the fluorescence intensity was changed according to the change of the component even after tooth whitening, indicating a relationship with whitening. In particular, the variable (b* value) of the yellowness of the teeth in the fluorescence photo was a variable related to minerals that also affect the whitening of teeth, and it was used as an auxiliary in natural color to help predict the whitening effect. Therefore, it was also possible to confirm the possibility of helping in the decision-making to distinguish between teeth that are likely to have a whitening effect and teeth that are likely to not work well by using a combination of a white photo and a fluorescence photo indicating the tone of the teeth.

Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto, and various modifications and variations are possible without departing from the technical spirit of the present invention described in the claims. It will be obvious to those of ordinary skill in the field.

Claims (18)

A method of providing information for predicting a tooth whitening effect, comprising the step of taking at least one of a white photo and a fluorescence photo of a tooth using quantitative light-induced fluorescence (QLF). The method of claim 1,
The teeth are central incisors (incisors), lateral incisors (incisors), canines (canines), premolars (small molars), or molars (large molars). The method of claim 1,
The step of photographing is to take both a white photograph and a fluorescent photograph. The method of claim 1,
The method of providing information further comprising the step of measuring at least one of an L* value, a* value, and b* value from the white photo or the fluorescence photo. The method of claim 4,
At least one of the L* value, a* value, and b* value is a value measured at one spot or an average value of values measured at a plurality of spots in the white photo or the fluorescent photo. The method of claim 5,
The spot is a circular shape having a diameter of 0.1 to 10 cm, information providing method. The method of claim 4,
The method of providing information further comprising the step of measuring a total color difference of ΔE* by substituting the L* value, a* value, and b* value obtained from each of the white photo and the fluorescence photo into the following Equation 1;
[Equation 1]
△E*= (A×WL* + B×Wa* + C×Wb*)-(D×FL* + E×Fa* + F×Fb*) + G
In Equation 1 above,
A is a rational number of -0.38 to -0.18, B is a rational number of 0.52 to 0.72, C is a rational number of 0.82 to 1.2, D is a rational number of 0.22 to 0.42, E is a rational number of 0.85 to 0.95 And F is a rational number of 0.10 to 0.30, G is a rational number of 15 to 20, and each of WL*, Wa* and Wb* is an L* value, a* value, and b* value obtained from the white photograph. , Each of the FL*, Fa* and Fb* is an L* value, a* value, and b* value obtained from the fluorescence photograph. The method of claim 7,
An information providing method that predicts that the higher the ΔE* value, which is the total color difference obtained from Equation 1 above, the higher the tooth whitening efficiency. The method of claim 4,
When the L* value measured from the white photo is 52 to 53 or less, and the b* value measured from the white photo is 8 to 9 or less, the tooth whitening efficiency is predicted to be high. The method of claim 4,
When the L* value measured from the white photo is greater than 52 to 53, and the b* value measured from the fluorescence photo is greater than 10 to 11, the method of predicting that the tooth whitening efficiency will be low. A photographing unit for photographing at least one of a white photo and a fluorescence photo of a tooth using quantitative light-induced fluorescence (QLF);
An input unit for inputting a color tone value measured from at least one of a white photo and a fluorescence photo of the tooth obtained by the photographing unit; And
An information providing device for predicting the effect of whitening teeth, comprising a calculation unit for predicting the whitening effect of the teeth from the color tone value obtained from the input unit. The method of claim 11,
The photographing unit, an information providing device for taking both a white photo and a fluorescent photo. The method of claim 11,
The input unit inputs at least one of an L* value, a* value, and b* value measured from the white photo or the fluorescence photo. The method of claim 13,
In the calculation unit, the L* value, a* value, and b* value obtained from each of the white photo and the fluorescence photo input from the input unit are substituted into Equation 1 below to measure the total color difference ΔE* value. Devices provided:
[Equation 1]
△E*= (A×WL* + B×Wa* + C×Wb*)-(D×FL* + E×Fa* + F×Fb*) + G
In Equation 1 above,
A is a rational number of -0.38 to -0.18, B is a rational number of 0.52 to 0.72, C is a rational number of 0.82 to 1.2, D is a rational number of 0.22 to 0.42, E is a rational number of 0.85 to 0.95 And F is a rational number of 0.10 to 0.30, G is a rational number of 15 to 20, and each of WL*, Wa* and Wb* is an L* value, a* value, and b* value obtained from the white photograph. , Each of the FL*, Fa* and Fb* is an L* value, a* value, and b* value obtained from the fluorescence photograph. The method of claim 14,
The operation unit predicts that the tooth whitening efficiency will be high when the total color difference ΔE* obtained from Equation 1 is 2 or more. The method of claim 13,
In the operation unit, when the L* value measured from the white photo input from the input unit is 52 to 53 or less, and the b* value measured from the white photo is 8 to 9 or less, predicting that the tooth whitening efficiency will be high, Information providing device. The method of claim 13,
In the operation unit, when the L* value measured from the white photo input from the input unit is 52 to 53 or more, and the b* value measured from the fluorescence photo is 10 to 11 or more, the tooth whitening efficiency is predicted to be low. , Information providing device. The method of claim 11,
The device includes: a display unit for displaying a result evaluated by the operation unit;
A memory capable of storing a program for the operation of the input unit or the operation unit, and temporarily storing input/output data;
Storage including volatile or nonvolatile storage media; And
A network interface that enables wired or wireless communication with other terminals through a network; An information providing device further comprising at least one of.

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