Objectives: To develop an automated procedure to detect patient motion on the projection images acquired during a cone beam computed tomography (CBCT) scan and to evaluate the method's feasibility on small real-world CBCT images in relation to visual assessment.
Methods: Based on optical flow theory, software was developed using the sequence of the projection images of a CBCT machine for automated detection of patient motion. Averaged acceleration vectors were used as measurement data and compared with visual assessment of the projection images displayed as video. Seventy-nine CBCT data sets (small field-of-view: 40 mm) from our patient database were selected in a sequential fashion and evaluated with the software.
Results: 10 out of 79 (13%) were allocated to a patient movement. A threshold of 0.4 pixel/frame transition was empirically determined as indicating motion by visual assessment of the image sequence. Relative to this standard of reference, the software reached 80% sensitivity versus 67% specificity.
Conclusions: Optical flow seems to be an efficient concept for automated detection of patient motion on the projection images acquired during a CBCT scan.
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