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Respiratory Motion Compensation Using Diaphragm Tracking for Cone-Beam C-Arm CT: A Simulation and a Phantom Study
Author(s) -
Marco Bögel,
Hannes Hofmann,
Joachim Hornegger,
Rebecca Fahrig,
Stefan Britzen,
Andreas Maier
Publication year - 2013
Publication title -
international journal of biomedical imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.626
H-Index - 41
eISSN - 1687-4196
pISSN - 1687-4188
DOI - 10.1155/2013/520540
Subject(s) - imaging phantom , ground truth , computer vision , image quality , artificial intelligence , computer science , diaphragm (acoustics) , motion compensation , visibility , projection (relational algebra) , match moving , motion (physics) , medicine , nuclear medicine , physics , image (mathematics) , acoustics , optics , algorithm , loudspeaker
Long acquisition times lead to image artifacts in thoracic C-arm CT. Motion blur caused by respiratory motion leads to decreased image quality in many clinical applications. We introduce an image-based method to estimate and compensate respiratory motion in C-arm CT based on diaphragm motion. In order to estimate respiratory motion, we track the contour of the diaphragm in the projection image sequence. Using a motion corrected triangulation approach on the diaphragm vertex, we are able to estimate a motion signal. The estimated motion signal is used to compensate for respiratory motion in the target region, for example, heart or lungs. First, we evaluated our approach in a simulation study using XCAT. As ground truth data was available, a quantitative evaluation was performed. We observed an improvement of about 14% using the structural similarity index. In a real phantom study, using the artiCHEST phantom, we investigated the visibility of bronchial tubes in a porcine lung. Compared to an uncompensated scan, the visibility of bronchial structures is improved drastically. Preliminary results indicate that this kind of motion compensation can deliver a first step in reconstruction image quality improvement. Compared to ground truth data, image quality is still considerably reduced.

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