Literature DB >> 16140487

A novel method of automated skull registration for forensic facial approximation.

W D Turner1, R E B Brown, T P Kelliher, P H Tu, M A Taister, K W P Miller.   

Abstract

Modern forensic facial reconstruction techniques are based on an understanding of skeletal variation and tissue depths. These techniques rely upon a skilled practitioner interpreting limited data. To (i) increase the amount of data available and (ii) lessen the subjective interpretation, we use medical imaging and statistical techniques. We introduce a software tool, reality enhancement/facial approximation by computational estimation (RE/FACE) for computer-based forensic facial reconstruction. The tool applies innovative computer-based techniques to a database of human head computed tomography (CT) scans in order to derive a statistical approximation of the soft tissue structure of a questioned skull. A core component of this tool is an algorithm for removing the variation in facial structure due to skeletal variation. This method uses models derived from the CT scans and does not require manual measurement or placement of landmarks. It does not require tissue-depth tables, can be tailored to specific racial categories by adding CT scans, and removes much of the subjectivity of manual reconstructions.

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Mesh:

Year:  2005        PMID: 16140487     DOI: 10.1016/j.forsciint.2004.10.003

Source DB:  PubMed          Journal:  Forensic Sci Int        ISSN: 0379-0738            Impact factor:   2.395


  8 in total

1.  Landmark-free geometric methods in biological shape analysis.

Authors:  Patrice Koehl; Joel Hass
Journal:  J R Soc Interface       Date:  2015-12-06       Impact factor: 4.118

2.  Using Computed Tomography (CT) Data to Build 3D Resources for Forensic Craniofacial Identification.

Authors:  Terrie Simmons-Ehrhardt; Catyana R S Falsetti; Anthony B Falsetti
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

3.  Sex determination with morphological characteristics of the skull by using 3D modeling techniques in computerized tomography.

Authors:  Ayse Kurtulus Dereli; Volkan Zeybek; Ergin Sagtas; Hande Senol; Hakan Abdullah Ozgul; Kemalettin Acar
Journal:  Forensic Sci Med Pathol       Date:  2018-09-19       Impact factor: 2.007

4.  Cranial and facial inter-landmark distances and tissue depth dataset from computed tomography scans of 388 living persons.

Authors:  Terrie L Simmons-Ehrhardt; Connie L Parks; Keith L Monson
Journal:  Data Brief       Date:  2022-05-29

Review 5.  An overview of the latest developments in facial imaging.

Authors:  Carl N Stephan; Jodi M Caple; Pierre Guyomarc'h; Peter Claes
Journal:  Forensic Sci Res       Date:  2018-10-29

6.  A method for automatic forensic facial reconstruction based on dense statistics of soft tissue thickness.

Authors:  Thomas Gietzen; Robert Brylka; Jascha Achenbach; Katja Zum Hebel; Elmar Schömer; Mario Botsch; Ulrich Schwanecke; Ralf Schulze
Journal:  PLoS One       Date:  2019-01-23       Impact factor: 3.240

7.  Craniofacial Reconstruction Method Based on Region Fusion Strategy.

Authors:  Yang Wen; Zhou Mingquan; Lin Pengyue; Geng Guohua; Liu Xiaoning; Li Kang
Journal:  Biomed Res Int       Date:  2020-12-04       Impact factor: 3.411

8.  Assessment of accuracy and recognition of three-dimensional computerized forensic craniofacial reconstruction.

Authors:  Geraldo Elias Miranda; Caroline Wilkinson; Mark Roughley; Thiago Leite Beaini; Rodolfo Francisco Haltenhoff Melani
Journal:  PLoS One       Date:  2018-05-02       Impact factor: 3.240

  8 in total

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