Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Automatic detection of patient motion in cone-beam computed tomography
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
ECG-gated interventional cardiac reconstruction for non- periodic motion
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part I
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Cone-beam X-Ray systems strictly depend on the imaged object being stationary over the entire acquisition process. Even slight patient motion can affect the quality of the final 3D reconstruction. It would be desirable to be able to discover and model patient motion right from the actual projection images, in order to take it into account during reconstruction. However, while the source-detector arrangement is rotating around the patient, it is difficult to separate this motion from the additional patient motion. We present a novel similarity metric for successive X-Ray projections, which is able to distinguish between the expected rotational and additional sources of motion. We quantitatively evaluate it on simulated dental cone-beam X-Rays and qualitatively demonstrate its performance on real patient data.