Dual fluoroscopic imaging and model-based tracking accuracy of arthrokinematic outcome metrics with and without frame interpolation

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

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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.