Literature DB >> 21595689

Application of superimposition-based personal identification using skull computed tomography images.

Masuko Ishii1, Kazuhiro Yayama, Hisako Motani, Ayaka Sakuma, Daisuke Yasjima, Mutumi Hayakawa, Seiji Yamamoto, Hirotaro Iwase.   

Abstract

Superimposition has been applied to skulls of unidentified skeletonized corpses as a personal identification method. The current method involves layering of a skull and a facial image of a suspected person and thus requires a real skeletonized skull. In this study, we scanned skulls of skeletonized corpses by computed tomography (CT), reconstructed three-dimensional (3D) images of skulls from the CT images, and superimposed the 3D images with facial images of the corresponding persons taken in their lives. Superimposition using 3D-reconstructed skull images demonstrated, as did superimposition using real skulls, an adequate degree of morphological consistency between the 3D-reconstructed skulls and persons in the facial images. Three-dimensional skull images reconstructed from CT images can be saved as data files and the use of these images in superimposition is effective for personal identification of unidentified bodies.
© 2011 American Academy of Forensic Sciences.

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Year:  2011        PMID: 21595689     DOI: 10.1111/j.1556-4029.2011.01797.x

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


  3 in total

1.  Reliability of frontal sinus by cone beam-computed tomography (CBCT) for individual identification.

Authors:  Gianguido Cossellu; Stefano De Luca; Roberto Biagi; Giampietro Farronato; Mariano Cingolani; Luigi Ferrante; Roberto Cameriere
Journal:  Radiol Med       Date:  2015-05-16       Impact factor: 3.469

2.  The conclusive role of postmortem computed tomography (CT) of the skull and computer-assisted superimposition in identification of an unknown body.

Authors:  Dorota Lorkiewicz-Muszyńska; Wojciech Kociemba; Czesław Żaba; Marzena Łabęcka; Małgorzata Koralewska-Kordel; Monica Abreu-Głowacka; Agnieszka Przystańska
Journal:  Int J Legal Med       Date:  2012-12-13       Impact factor: 2.686

3.  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

  3 in total

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