Evaluating Cranial Nonmetric Traits in Mummies from Pachacamac, Peru: The Utility of Semi-Automated Image Segmentation in Paleoradiology
Abstract
Anthropologists employ biodistance analysis to understand past population interactions and relatedness. The objectives of this thesis are twofold: to determine whether a sample of five mummies from the pilgrimage centre, Pachacamac, on the Central Coast of Peru comprised local or non-local individuals through an analysis of cranial nonmetric traits using comparative samples from the North and Central Coasts of Peru and Chile; and to test the utility of machine-learning-based image segmentation in the image analysis software, Dragonfly, to automatically segment CT scans of the mummies such that the cranial nonmetric traits are visible. Results show that while fully automated segmentation was not achieved, a semi-automated procedure was adequate for visualizing and scoring the skulls and saved time over manual segmentation methods. The sample from Pachacamac was too small to make significant inter-site comparisons, but a broader regional analysis suggests there are significant biological differences between geographical regions along the coast.