CT Auto-calibration by Consistent Contours

This paper discusses a novel strategy for estimating
projection matrices of a computed tomography using object
contours in projection images. We formulate mathematical conditions
for projection parameter consistency based on contour
detection and tracking in 2D. We derive a global optimization
problem and a greedy optimizer herein. Applying the approach
for motion detection shows an average reduction of motion error
in object space down to 0.15mm in a standard dental conebeam
CT setup. Evaluation is performed on simulated data
with different motion types and object shapes, and considers
the influence of noisy contour data. The accuracy of estimation
is linked to sample resolution, number and distinctiveness of
imaged objects, and accuracy of input data. Our strategy is robust
towards inaccurate initialization and truncated data.