A standardization model based on image recognition for performance evaluation of an oral scanner

Sang Wan Seo, Wan Sun Lee, Jae Young Byun, Kyu Bok Lee

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

PURPOSE. Accurate information is essential in dentistry. The image information of missing teeth is used inoptically based medical equipment in prosthodontic treatment. To evaluate oral scanners, the standardizedmodel was examined from cases of image recognition errors of linear discriminant analysis (LDA), and a modelthat combines the variables with reference to ISO 12836:2015 was designed. MATERIALS AND METHODS. Thebasic model was fabricated by applying 4 factors to the tooth profile (chamfer, groove, curve, and square) andthe bottom surface. Photo-type and video-type scanners were used to analyze 3D images after image capture.The scans were performed several times according to the prescribed sequence to distinguish the model from theone that did not form, and the results confirmed it to be the best. RESULTS. In the case of the initial basic model,a 3D shape could not be obtained by scanning even if several shots were taken. Subsequently, the recognitionrate of the image was improved with every variable factor, and the difference depends on the tooth profile andthe pattern of the floor surface. CONCLUSION. Based on the recognition error of the LDA, the recognition ratedecreases when the model has a similar pattern. Therefore, to obtain the accurate 3D data, the difference of eachclass needs to be provided when developing a standardized model.

Original languageEnglish
Pages (from-to)409-415
Number of pages7
JournalJournal of Advanced Prosthodontics
Volume9
Issue number6
DOIs
StatePublished - 1 Dec 2017

Keywords

  • 3D scanner
  • Image recognition
  • Linear discriminant analysis (LDA)
  • Standardization model

Fingerprint

Dive into the research topics of 'A standardization model based on image recognition for performance evaluation of an oral scanner'. Together they form a unique fingerprint.

Cite this