Christoph Forman1,
2, Davide Piccini3, 4, Joachim Hornegger, 25,
Michael O. Zenge6
1Pattern
Recognition Lab, Friedrich-Alexander-University Erlangen-Nrnberg, Erlangen,
Germany; 2Erlangen Graduate School in Advanced Optical
Technologies (SAOT), Friedrich-Alexander-Universitt Erlangen-Nrnberg,
Erlangen, Germany; 3Advanced Clinical Imaging Technology, Siemens
Healthcare IM S AW, Lausanne, Switzerland; 4CIBM-AIT, Ecole
Polytechnique Fdrale de Lausanne, Lausanne, Switzerland; 5Pattern
Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universitt
Erlangen-Nrnberg, Erlangen, Germany; 6Healthcare Sector, Siemens
AG, Erlangen, Germany
The experience of an extended number of volunteer experiments revealed that a respiratory motion detection by tracking the heart in SI projections can be degraded by several factors, e.g. suboptimal fat saturation, which may result in motion artefacts in the reconstructed images. By leaving the paradigm to correct for motion directly from the feedback of the projections behind, we propose a more robust method for the binning of the SI projections into respiratory phases. The robustness of the new approach was demonstrated in experiments with 10 healthy volunteers. The proposed method showed a high correlation to the conventional navigator.