Literature DB >> 26832374

"High-precision, reconstructed 3D model" of skull scanned by conebeam CT: Reproducibility verified using CAD/CAM data.

Seiko Katsumura1, Keita Sato2, Tomoko Ikawa3, Keiko Yamamura4, Eriko Ando3, Yuko Shigeta3, Takumi Ogawa3.   

Abstract

Computed tomography (CT) scanning has recently been introduced into forensic medicine and dentistry. However, the presence of metal restorations in the dentition can adversely affect the quality of three-dimensional reconstruction from CT scans. In this study, we aimed to evaluate the reproducibility of a "high-precision, reconstructed 3D model" obtained from a conebeam CT scan of dentition, a method that might be particularly helpful in forensic medicine. We took conebeam CT and helical CT images of three dry skulls marked with 47 measuring points; reconstructed three-dimensional images; and measured the distances between the points in the 3D images with a computer-aided design/computer-aided manufacturing (CAD/CAM) marker. We found that in comparison with the helical CT, conebeam CT is capable of reproducing measurements closer to those obtained from the actual samples. In conclusion, our study indicated that the image-reproduction from a conebeam CT scan was more accurate than that from a helical CT scan. Furthermore, the "high-precision reconstructed 3D model" facilitates reliable visualization of full-sized oral and maxillofacial regions in both helical and conebeam CT scans.
Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Conebeam CT; Dental treatment; Helical CT; High-precision; Identification; Metal artifact; Reconstructed 3D model

Mesh:

Year:  2015        PMID: 26832374     DOI: 10.1016/j.legalmed.2015.11.007

Source DB:  PubMed          Journal:  Leg Med (Tokyo)        ISSN: 1344-6223            Impact factor:   1.376


  1 in total

1.  Development of an artificial intelligence-based algorithm to classify images acquired with an intraoral scanner of individual molar teeth into three categories.

Authors:  Nozomi Eto; Junichi Yamazoe; Akiko Tsuji; Naohisa Wada; Noriaki Ikeda
Journal:  PLoS One       Date:  2022-01-07       Impact factor: 3.240

  1 in total

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