Dual fluoroscopic imaging and model-based tracking accuracy of arthrokinematic outcome metrics with and without frame interpolation
Conference Year
January 2022
Abstract
An innovative approach to quantifying arthrokinematics (joint surface interactions) following joint trauma involves using a dual fluoroscopic imaging system (DFIS) with model-based tracking (MBT). While highly accurate, the DFIS with MBT approach is time-consuming and susceptible to human error (i.e. semi-automatic). Therefore, this study aimed to quantify the error associated with the semi-automatic analysis and to understand the effects of employing interpolation for reducing analysis time. We compared arthrokinematic metrics calculated via multiple DFIS-MBT analyses (i.e. human error) with/without interpolation to a gold standard technique. The results quantify human error and suggest that interpolation may be used without sacrificing accuracy.
Primary Faculty Mentor Name
Niccolo Fiorentino
Graduate Student Mentors
John Ramsdell
Faculty/Staff Collaborators
Bruce Beynnon
Status
Undergraduate
Student College
College of Engineering and Mathematical Sciences
Program/Major
Biomedical Engineering
Primary Research Category
Engineering & Physical Sciences
Secondary Research Category
Health Sciences
Dual fluoroscopic imaging and model-based tracking accuracy of arthrokinematic outcome metrics with and without frame interpolation
An innovative approach to quantifying arthrokinematics (joint surface interactions) following joint trauma involves using a dual fluoroscopic imaging system (DFIS) with model-based tracking (MBT). While highly accurate, the DFIS with MBT approach is time-consuming and susceptible to human error (i.e. semi-automatic). Therefore, this study aimed to quantify the error associated with the semi-automatic analysis and to understand the effects of employing interpolation for reducing analysis time. We compared arthrokinematic metrics calculated via multiple DFIS-MBT analyses (i.e. human error) with/without interpolation to a gold standard technique. The results quantify human error and suggest that interpolation may be used without sacrificing accuracy.