Automated detection of patient movement during a CBCT scan based on the projection data

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 the...

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Bibliographic Details
Published in:Oral surgery, oral medicine, oral pathology and oral radiology oral medicine, oral pathology and oral radiology, 2015-04, Vol.119 (4), p.468-472
Main Authors: Schulze, Ralf K.W., Prof Dr med dent, Michel, Michel, Dr med dent, Schwanecke, Ulrich, Prof Dr rer nat
Format: Article
Language:English
Subjects:
Algorithms
Cone-Beam Computed Tomography
Dentistry
Feasibility Studies
Humans
Imaging, Three-Dimensional
Movement
Phantoms, Imaging
Radiographic Image Interpretation, Computer-Assisted
Sensitivity and Specificity
Software
Surgery
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Summary: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.
ISSN:2212-4403
2212-4411
DOI:10.1016/j.oooo.2014.12.008