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Computerized Reconstruction of Fragmentary Skeletal Remains for Purposes of Extracting Osteometric Measurements and Estimating MNI

NCJ Number
249948
Date Published
June 2016
Length
33 pages
Annotation
This project developed a computer software that enables forensic anthropologists to quantify and reconstruct fragmentary human skeletal remains (crania, pelves, humeri, and femora) from three dimensional surface files generated by computed tomography or laser scans.
Abstract

The software enables the user to visualize fragmentary elements and reject or accept them, followed by initial alignment of fragmentary elements with a three-dimensional statistical template for each bone. After accepting the alignment of the elements, the software merges the elements, producing a fully reconstructed bone. Measurements can then be conducted by the user for application to regression equations, discriminate functions, or to use with software such as Fordisc 3.0. In developing and validating the software, 24,569 bone fragments from the Morton Shell Mound from the gulf coast of Louisiana were sorted; 18,373 fragments were coded; 1,232 fragments were digitized; and 2,061 fragments were CT scanned. The developed software was validated by using both simulated data and real data from the Morton collection. Software was compared to GIS; same fragment IDs were matched using both systems; and fragments were placed in comparable location on the template. The reconstruction results on simulated data were less than 2 mm mean RMS error for pelvis, skull, humerus, and femur. The developed system produced similar results when compared to GIS when looking at both the ID of matched fragments and location of matched fragments on the template. The developed application significantly improves forensic anthropologists' and crime-scene investigators' ability to reconstruct mass disasters, comingled mass graves, and highly fragmentary individual burials or surface scatters. 5 tables, 29 figures, 16 references, and appended software usage example

Date Published: June 1, 2016