Integrated contour detection and pose estimation for fluoroscopic analysis of knee implants

Abstract

With fluoroscopic analysis of knee implant kinematics the implant contour must be detected in each image frame, followed by estimation of the implant pose. With a large number of possibly low-quality images, the contour detection is a time-consuming bottleneck. The present paper proposes an automated contour detection method, which is integrated in the pose estimation. In a phantom experiment the automated method was compared with a standard method, which uses manual selection of correct contour parts. Both methods demonstrated comparable precision, with a minor difference in the Y-position (0.08 mm versus 0.06 mm). The precision of each method was so small (below 0.2 mm and 0.3°) that both are sufficiently accurate for clinical research purposes. The efficiency of both methods was assessed on six clinical datasets. With the automated method the observer spent 1.5 min per image, significantly less than 3.9 min with the standard method. A Bland–Altman analysis between the methods demonstrated no discernible trends in the relative femoral poses. The threefold increase in efficiency demonstrates that a pose estimation approach with integrated contour detection is more intuitive than a standard method. It eliminates most of the manual work in fluoroscopic analysis, with sufficient precision for clinical research purposes.