Detecting patient motion in projection space for cone-beam computed tomography

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Abstract

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. © 2011 Springer-Verlag.

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APA

Wein, W., & Ladikos, A. (2011). Detecting patient motion in projection space for cone-beam computed tomography. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6891 LNCS, pp. 516–523). https://doi.org/10.1007/978-3-642-23623-5_65

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