Author ORCID Identifier

Defense Date


Document Type


Degree Name

Doctor of Philosophy


Biomedical Engineering

First Advisor

Jennifer Wayne, Ph.D.

Second Advisor

Paul Wetzel, Ph.D.

Third Advisor

Niraj Kalore, M.D.

Fourth Advisor

Dianne Pawluk, Ph.D.

Fifth Advisor

Alen Docef, Ph.D.


Image recognition and computer vision are becoming increasingly useful for diagnostic and surgical planning purposes. Analyses of patient morphology can be performed much more quickly and reliably with algorithmic assistance. Traditional measurements of the hip involve visual inspection of patient radiographs or hand calculation with software assistance. In the most extreme cases, estimates of bone orientation are made via palpation of a patient’s hip. There is the possibility for significant improvements in reliability if measurements can be made in the absence of human interpretation. As many of these techniques require CT scans as a prerequisite, all of the necessary information is available for automation of patient measurement. A software suite has been created that is capable of performing a set of hip diagnostic measurements directly on patient CT data. This set of algorithms first segments the CT scan, creating 3D surface models of the femur and pelvis. Feature recognition algorithms then detect the major bony landmarks and use these to perform a set of clinically-relevant measurements. This information can then be applied to inform any hip reconstructive surgery. Measurements of acetabular and femoral orientation performed by the software were validated against previous studies employing the same patient cohort. Sacral orientation measurements were validated through manual measurement of a subset of the population. The hip analysis suite described in this dissertation is capable of accurate and reliable assessment of the hip without any human intervention. If implemented to inform surgical planning, this has the possibility of improving the outcome of hip reconstructive surgery.


© Nathan J. Veilleux

Is Part Of

VCU University Archives

Is Part Of

VCU Theses and Dissertations

Date of Submission


Available for download on Thursday, May 15, 2025