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                            Library & Multimedia
 Success Story: Uncovering Key Details of Skeletal Remains Through 3D-ID Software
NCJ Number
              252526

Date Published

January 2019
Length
              2 pages
Annotation
              Based on interdisciplinary collaboration among anthropology, computer science, and statistics researchers from North Carolina State University and Florida State University, this article reports on the development and benefits for forensic anthropology of geometric morphometric (GM) analysis with 3D-ID, a no-cost software that enables the forensic anthropologist to estimate sex and ancestry for unknown remains using GM methods.
Abstract
              Traditionally, the methods used to characterize the shape and size of a skull involve multivariate statistical analysis techniques that measure disparate linear distances between anatomical landmarks on the skull; however, this approach provides limited information on the shape of the skull, since the linear distances are measured in two dimensions rather than in relation to other measurements. GM analysis records the same anatomical landmarks, but in relation to each other in three dimensions, thus providing a more biologically informative perspective of the skull and facilitating the estimation of sex and ancestry for unknown individuals. The use of GM is challenging, however, since the coordinate data associated with the anatomical landmarks must be standardized for direct comparison. This requires additional analysis. In order to facilitate the use of GM in forensic anthropology, Dr. Ann Ross and Dr, Dennis Slice developed 3D-ID, a software that enables a forensic anthropologist to estimate sex and ancestry for unknown crania, using GM methods. The software automatically standardizes the coordinate data from the GM measurements, simplifying analysis and saving time for the practitioner. The estimations are made by comparing coordinate data obtained from unknown crania to those of a collection of reference samples procured from forensic casework, museums, and collaborators. Future directions are outlined.
      
  
          Additional Details
Grant Number(s)
        2016-MU-BX-K110


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Publication Type
        Research (Applied/Empirical)
                                Report (Study/Research)
                                Report (Grant Sponsored)
                                Program/Project Description
                                Grants and Funding


  
  
        
  Award
        Forensic Technology Center of Excellence (FTCOE) FY17
    
  
  
Date Published: January 1, 2019
    
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