Robust Automatic Detection and Removal of Fiducial Projections in Fluoroscopy Images: An Integrated Solution

Automatic detection and removal of fiducial projections in fluoroscopy images is an essential prerequisite for fluoroscopy-based navigation and image-based 3D-2D registration. This paper presents an integrated solution to fulfill this task. A custom-designed calibration cage with a two-plane pattern of fiducials is utilized in our solution. The cage is attached to the C-arm image intensifier and the projections of the fiducials are automatically detected and removed by an on-line algorithm consisting of following 6 steps: image binarization, connected-component labeling, region classification, adaptive template matching, shape analysis, and fiducial projection removal. A similarity measure which is proposed previously for image-based 3D-2D registration is employed in the adaptive template matching to improve the accuracy of the detection. Shape analysis based on the geometrical constraints satisfied by those fiducials in the calibration cage is used to further improve the robustness of the detection. An image inpainting technique based on the fast marching method for level set applications is used to remove the detected fiducial projections. Our in vitro experiments show on average 4 seconds execution time on a Pentium IV machine, a zero false-detection rate, a miss-detection rate of 1.6 +/- 2.3%, and a sub-pixel locatization error.