Computed virtual models of anatomical structures are proving to be of increasing value in clinical medicine, education and research. With a variety of fields focused on craniofacial and pelvic anatomy there is a need for accurate anatomical models. Recent technological advancements in computer and medical imaging technologies have provided the tools necessary to develop three-dimensional (3D) functional models of human anatomy for use in medicine (surgical planning and education), forensics and engineering (computer-aided design (CAD) and finite element analysis). Traditionally caliper methodologies are used in the quantitative analysis of human anatomy. In order for experts in anatomy and morphometrics to accept a transition to 3D volumetric data, it must be first validated as anatomically accurate. The purpose of this project was to create anatomically accurate models of modern human anatomy through the use of 3D medical imaging, such as multislice computed tomography (CT), and 3D computer modeling and reconstruction. This dissertation attempts to validate the models and address current morphometric methodologies with four separate studies. The important results found in these studies were: 1) Medical image data such as computed tomography scans can be used to create high-resolution anatomically accurate 3D models for education and research purposes. These models can be used in morphometric studies through virtual quantitative analyses. 2) 3D virtual models of the human pelvis are 100% accurate in the estimation of sex in the pelvis, which represents an increase in accuracy over current field methods. 3) 3D virtual models of the human skull are 95.1% accurate in estimating sex in the skull, which represents an increase in accuracy over current field methods. 4) 3D models of craniofacial anatomy can be used for soft tissue depth analysis studies and clinical image data is more representative of living individuals. By testing the imaging and 3D modeling technologies at several levels, we developed new methods for accurately analyzing virtual anatomy for an array of disciplines.