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                            Library & Multimedia
 Open-source Tools for Dense Facial Tissue Depth Mapping (FTDM) of Computed Tomography Models
NCJ Number
              252054

Author(s)
          Terrie Simmons-Ehrhardt, Catyana Falsetti, Anthony B. Falsetti, Christopher J. Ehrhardt
Date Published

August 2018
Length
              40 pages
Annotation
              This paper describes tools for the production of dense facial tissue depth maps (FTDMs), using de-identified head computed tomography (CT) scans of modern Americans from the public repository, the Cancer Imaging Archives (TCLA), and the open-source program Meshlab.
Abstract
              CT scans of 43 females and 63 males from TCLA were segmented and converted to 3D skull and face models using Mimics; and they were exported as stereo lithography (STL) files. All subsequent processing steps were performed in Meshlab. Heads were transformed to a common orientation and coordinate system, using the coordinates of nasion, left orbitale, and left and right portion. Dense FTDMs were produced on hollowed, cropped face shells, using the Hausdorff sampling filter. This research project produced visual quantitative representations of the face and skull for forensic facial approximation research and practice that can be further analyzed or studied using free software. The presented tools can be applied to pre-existing CT scans, traditional or cone-beam, adult or younger individuals, with or without landmarks, and regardless of head orientation. This can be used for forensic applications and studies of facial variation and facial growth. Unlike other facial mapping studies, this method produced both skull and face points based on replicable geometric relationships, producing multiple data outputs that are easily read and software that is openly accessible. Materials and methods are described in detail. 8 figures, 1 table, and 65 references
      
  
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        Three-Dimensional Craniofacial Variation of Modern Americans: A Visual Reference to Supplement Facial Approximation Methods
    
  
  
Date Published: August 1, 2018
    
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