Technical note: unsupervised C-arm pose tracking with radiographic fiducial

Abstract

Purpose: 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.

Methods: 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.

Results: 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.

Conclusions: The C-arm pose tracking method was sufficiently accurate and robust on human patient data for subsequent 3D implant reconstruction.