Literature DB >> 21264365

Reliability and accuracy of Crystaleye spectrophotometric system.

Li Chen1, Jian Guo Tan, Jian Feng Zhou, Xu Yang, Yang Du, Fang Ping Wang.   

Abstract

OBJECTIVE: to develop an in vitro shade-measuring model to evaluate the reliability and accuracy of the Crystaleye spectrophotometric system, a newly developed spectrophotometer.
METHODS: four shade guides, VITA Classical, VITA 3D-Master, Chromascop and Vintage Halo NCC, were measured with the Crystaleye spectrophotometer in a standardised model, ten times for 107 shade tabs. The shade-matching results and the CIE L*a*b* values of the cervical, body and incisal regions for each measurement were automatically analysed using the supporting software. Reliability and accuracy were calculated for each shade tab both in percentage and in colour difference (ΔE). Difference was analysed by one-way ANOVA in the cervical, body and incisal regions.
RESULTS: range of reliability was 88.81% to 98.97% and 0.13 to 0.24 ΔE units, and that of accuracy was 44.05% to 91.25% and 1.03 to 1.89 ΔE units. Significant differences in reliability and accuracy were found between the body region and the cervical and incisal regions. Comparisons made among regions and shade guides revealed that evaluation in ΔE was prone to disclose the differences.
CONCLUSION: measurements with the Crystaleye spectrophotometer had similar, high reliability in different shade guides and regions, indicating predictable repeated measurements. Accuracy in the body region was high and less variable compared with the cervical and incisal regions.

Mesh:

Year:  2010        PMID: 21264365

Source DB:  PubMed          Journal:  Chin J Dent Res        ISSN: 1462-6446


  2 in total

1.  Interdevice agreement of eight equivalent dental color measurement devices.

Authors:  M Weyhrauch; C Igiel; A M Pabst; S Wentaschek; H Scheller; K M Lehmann
Journal:  Clin Oral Investig       Date:  2015-03-24       Impact factor: 3.573

2.  The prediction in computer color matching of dentistry based on GA+BP neural network.

Authors:  Haisheng Li; Long Lai; Li Chen; Cheng Lu; Qiang Cai
Journal:  Comput Math Methods Med       Date:  2015-03-22       Impact factor: 2.238

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.