PublicationDetail

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

A. Keil, C. Wachinger, G. Brinker, S. Thesen, N. Navab
Patient Position Detection for SAR Optimization in Magnetic Resonance Imaging
Proc. of Medical Image Computing and Computer-Assisted Intervention (MICCAI 2006), Copenhagen, Denmark, October 2006. The original publication is available online at www.springerlink.com. (bib)

Although magnetic resonance imaging is considered to be non-invasive, there is at least one effect on the patient which has to be monitored: The heating which is generated by absorbed radio frequency (RF) power. It is described using the specific absorption rate (SAR). In order to obey legal limits for these SAR values, the scanner’s duty cycle has to be adjusted. The limiting factor depends on the patient’s position with respect to the scanner. Detection of this position allows a better adjustment of the RF power resulting in an improved scan performance and image quality. In this paper, we propose real-time methods for accurately detecting the patient’s position with respect to the scanner. MR data of thirteen test persons acquired using a new “move during scan” protocol which provides low resolution MR data during the initial movement of the patient bed into the scanner, is used to validate the detection algorithm. When being integrated, our results would enable automatic SAR optimization within the usual acquisition workflow at no extra cost.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each authors copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.



Edit | Attach | Refresh | Diffs | More | Revision r1.11 - 19 Jul 2016 - 16:26 - NassirNavab

Lehrstuhl für Computer Aided Medical Procedures & Augmented Reality    rss.gif