A Digital Shade-Matching Device for Dental Color Determination Using the Support Vector Machine Algorithm

Abstract

In this study, we developed a digital shade-matching device for dental color determination using the support vector machine (SVM) algorithm. Shade-matching was performed using shade tabs. For the hardware, the typically used intraoral camera was modified to apply the cross-polarization scheme and block the light from outside, which can lead to shade-matching errors. For reliable experiments, a precise robot arm with ±0.1 mm position repeatability and a specially designed jig to fix the position of the VITA 3D-master (3D) shade tabs were used. For consistent color performance, color calibration was performed with five standard colors having color values as the mean color values of the five shade tabs of the 3D. By using the SVM algorithm, hyperplanes and support vectors for 3D shade tabs were obtained with a database organized using five developed devices. Subsequently, shade matching was performed by measuring 3D shade tabs, as opposed to real teeth, with three additional devices. On average, more than 90% matching accuracy and a less than 1% failure rate were achieved with all devices for 10 measurements. In addition, we compared the classification algorithm with other classification algorithms, such as logistic regression, random forest, and k-nearest neighbors, using the leave-pair-out cross-validation method to verify the classification performance of the SVM algorithm. Our proposed scheme can be an optimum solution for the quantitative measurement of tooth color with high accuracy.

Tooth shade analysis and selection in prosthodontics: A systematic review and meta-analysis

“…[ 12 ] Kim et al . [ 11 ] developed the method of digital shade by modifying the intraoral camera. The two linear polarizer were placed in front of the light source (cross-polarization) of an intraoral camera which blocks the light from outside.…”

“…They further stated that spectrophotometer and colorimeters do not provide true image information to measure the exact value of tooth color. [ 11 ] A cross-sectional study on 400 individuals reported that the most common shade of maxillary and mandibular incisors in younger age male is A2 for Vita Lumina, 2R2.5 for Vita 3D master, and 140 for Chromascop shade guide and for females is A1 for Vita Lumina, 1M2 for Vita 3D master, and 120 for Chromascop shade guide. In the advanced age group, the most common shade for the same teeth is A2 for Vita Lumina, 2R2.5 for Vita 3D master, and 140 for Chromascop shade guide.…”

“…The computer tooth image has more clarity, thus it reduces many subjective errors of visual shade guide method. [ 11 12 ] Recently, mobile application was evaluated for color matching, however the accuracy was inferior to that of Vita classical shade tab. [ 13 ]…”

Dental Shade Matching: Recent Technologies and Future Smart Applications

“…But still below the accuracy of the reference spectrophotometer system [10] lighting conditions, and results showed that the intraoral scanner obtained a significant higher mean repeatability of dental shade matching compared to the visual method [20]. Kim, et al, developed a digital shade-matching device utilising a modified intraoral camera to measure 3D shade tabs, which reported more than 90% matching accuracy and less than 1% failure rate [21].…”

A water destructible SnS2QD/PVA film based transient multifunctional sensor and machine learning assisted stimulus identification for non-invasive personal care diagnostics

“…17 In another reported work, the digital shade matching device for dental colour determination was adopted to identify the optimal solution for quantitative tooth colour measurement. 18 The above literature suggests that machine learning has huge potential for the frontend classification of the multifunctional sensor but the study towards it remains unexplored.…”