Prospective Respiration Detection in Magnetic Resonance Imaging by a non-interfering Noise Navigator
Publication date
2018-08
Editors
Advisors
Supervisors
Document Type
Article
Metadata
Show full item recordCollections
License
taverne
Abstract
Passive monitoring of the thermal noise variances of the channels of a receive array was shown to reveal respiratory motion of the underlying anatomy, a so called 'noise navigator'. There is, however, an inevitable trade off between the accuracy and temporal resolution of the noise navigator due to its passive nature. A temporal filter has to be added to the noise navigator to accurately reveal respiration and retain temporal resolution. For real-time applications of the noise navigator, e.g., prospective motion correction or motion tracking, the added filter must be prospective. Thus a prospective Kalman filter was designed to predict respiration from the noise navigator without a temporal delay. The performance of the noise navigator enhanced by this prospective Kalman filter was explored and the robustness of the proposed method was assessed on healthy volunteers. The respiratory signal could be measured by the noise navigator independent of magnetic resonance acquisition. The calculated respiratory signal was qualitatively compared with the respiratory bellows. In addition, a strong linear relationship was found between the prospective noise navigator and a quantitative 2-D image navigator for measurements, including free and tasked breathing.
Keywords
Abdomen, Magnetic Resonance Imaging, Motion compensation and analysis, Tracking, magnetic resonance imaging, motion compensation and analysis, tracking, Taverne, Software, Radiological and Ultrasound Technology, Electrical and Electronic Engineering, Computer Science Applications
Citation
Navest, R J M, Andreychenko, A, Lagendijk, J J W & van den Berg, C A T 2018, 'Prospective Respiration Detection in Magnetic Resonance Imaging by a non-interfering Noise Navigator', IEEE Transactions on Medical Imaging, vol. 37, no. 8, pp. 1751-1760. https://doi.org/10.1109/TMI.2018.2808699