Technical Note: Unsupervised C‐arm pose tracking with radiographic fiducial

Abstract

C-arm fluoroscopy reconstruction, such as that used in prostate brachytherapy, requires that the relative poses of the individual C-arm fluoroscopy images must be known prior to reconstruction. Radiographic fiducials can provide excellent C-arm pose tracking, but they need to be segmented in the image. The authors report an automated and unsupervised method that does not require prior segmentation of the fiducial. The authors compute the individual C-arm poses relative to a stationary radiographic fiducial of known geometry. The authors register a filtered 2D fluoroscopy image of the fiducial to its 3D model by using image intensity alone without prior segmentation. To enhance the C-arm images, the authors investigated a three-step cascade filter and a line enhancement filter. The authors tested the method on a composite fiducial containing beads, straight lines, and ellipses. Ground-truth C-arm pose was provided by a clinically proven method. Using 111 clinical C-arm images and +/- 10 degrees and +/- 10 mm random perturbation around the ground-truth pose, a total of 2775 cases were evaluated. The average rotation and translation errors were 0.62 degrees (STD = 0.31 degrees) and 0.72 mm (STD = 0.55 mm) for the three-step filter and 0.67 degrees (STD = 0.40 degrees) and 0.87 mm (STD = 0.27 mm) using the line enhancement filter. The C-arm pose tracking method was sufficiently accurate and robust on human patient data for subsequent 3D implant reconstruction.