Literature DB >> 20002257

Radiographic recognition of dental implants as an aid to identifying the deceased.

John W Berketa1, Robert S Hirsch, Denice Higgins, Helen James.   

Abstract

This study was undertaken to determine if dental implants can be radiographically differentiated by company type to aid forensic identification of the deceased. Recognition of dental implants on intraoral radiographic images was assessed in a blind study using a radiographic examination guide to highlight differences between dental implants. Inter- and intra-examiner comparisons were conducted and a computer program (Implant Recognition System) was evaluated to see whether it improved the accuracy of implant recognition. The study found that dental implants could be radiographically differentiated by company type. The Implant Recognition System in its current form was of little benefit for radiographic assessment of dental implants for forensic odontologists. Prior knowledge of implant types, with a McNemar's statistical value of 92.9, proved to be most significant in identification.

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Year:  2009        PMID: 20002257     DOI: 10.1111/j.1556-4029.2009.01226.x

Source DB:  PubMed          Journal:  J Forensic Sci        ISSN: 0022-1198            Impact factor:   1.832


  6 in total

Review 1.  Forensic odontology involvement in disaster victim identification.

Authors:  John William Berketa; Helen James; Anthony W Lake
Journal:  Forensic Sci Med Pathol       Date:  2011-09-28       Impact factor: 2.007

2.  A pilot study in the recovery and recognition of non-osseointegrated dental implants following cremation.

Authors:  J Berketa; H James; V Marino
Journal:  J Forensic Odontostomatol       Date:  2011-12-01

Review 3.  Maximizing postmortem oral-facial data to assist identification following severe incineration.

Authors:  John W Berketa
Journal:  Forensic Sci Med Pathol       Date:  2013-10-25       Impact factor: 2.007

Review 4.  Prosthodontics an "arsenal" in forensic dentistry.

Authors:  Lakshmana Rao Bathala; Narendra Kumar Rachuri; Srinivas Rao Rayapati; Sudheer Kondaka
Journal:  J Forensic Dent Sci       Date:  2016 Sep-Dec

5.  A Performance Comparison between Automated Deep Learning and Dental Professionals in Classification of Dental Implant Systems from Dental Imaging: A Multi-Center Study.

Authors:  Jae-Hong Lee; Young-Taek Kim; Jong-Bin Lee; Seong-Nyum Jeong
Journal:  Diagnostics (Basel)       Date:  2020-11-07

6.  Efficacy of deep convolutional neural network algorithm for the identification and classification of dental implant systems, using panoramic and periapical radiographs: A pilot study.

Authors:  Jae-Hong Lee; Seong-Nyum Jeong
Journal:  Medicine (Baltimore)       Date:  2020-06-26       Impact factor: 1.817

  6 in total

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