Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Labeling of Anatomical Structures in MR FastView Images Using a Statistical Atlas
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
Manifold learning for patient position detection in MRI
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
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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.