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 project, we use 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.
Future developments seek an even more robust and accurate detection of more features of the patient than just head, neck, lung, and feet.
||C. Wachinger, D. Mateus, A. Keil, N. Navab
Manifold Learning for Patient Position Detection in MRI
IEEE International Symposium on Biomedical Imaging (ISBI), Rotterdam, The Netherlands, April 14 - 17 2010.
||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.
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