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Proceedings Paper

Automatic intrinsic cardiac and respiratory gating from cone-beam CT scans of the thorax region
Author(s): Andreas Hahn; Sebastian Sauppe; Michael Lell; Marc Kachelrieß
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Paper Abstract

We present a new algorithm that allows for raw data-based automated cardiac and respiratory intrinsic gating in cone-beam CT scans. It can be summarized in three steps: First, a median filter is applied to an initially reconstructed volume. The forward projection of this volume contains less motion information and is subtracted from the original projections. This results in new raw data that contain only moving and not static anatomy like bones, that would otherwise impede the cardiac or respiratory signal acquisition. All further steps are applied to these modified raw data. Second, the raw data are cropped to a region of interest (ROI). The ROI in the raw data is determined by the forward projection of a binary volume of interest (VOI) that includes the diaphragm for respiratory gating and most of the edge of the heart for cardiac gating. Third, the mean gray value in this ROI is calculated for every projection and the respiratory/cardiac signal is acquired using a bandpass filter. Steps two and three are carried out simultaneously for 64 or 1440 overlapping VOI inside the body for the respiratory or cardiac signal respectively. The signals acquired from each ROI are compared and the most consistent one is chosen as the desired cardiac or respiratory motion signal. Consistency is assessed by the standard deviation of the time between two maxima. The robustness and efficiency of the method is evaluated using simulated and measured patient data by computing the standard deviation of the mean signal difference between the ground truth and the intrinsic signal.

Paper Details

Date Published: 22 March 2016
PDF: 6 pages
Proc. SPIE 9783, Medical Imaging 2016: Physics of Medical Imaging, 97830S (22 March 2016); doi: 10.1117/12.2216224
Show Author Affiliations
Andreas Hahn, German Cancer Research Ctr. (Germany)
Sebastian Sauppe, German Cancer Research Ctr. (Germany)
Michael Lell, Friedrich-Alexander-Univ. Erlangen-Nürnberg (Germany)
Marc Kachelrieß, German Cancer Research Ctr. (Germany)


Published in SPIE Proceedings Vol. 9783:
Medical Imaging 2016: Physics of Medical Imaging
Despina Kontos; Thomas G. Flohr, Editor(s)

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