Abstract #3345

Machine learning based Magnetic tracking technique using a Mapping of the Magnetic Gradient Fields on a 3T MRI scanner

Benjamin Roussel^1,2, Joris Pascal³, Nicolas Weber^1,2, Philip Keller⁴, Antoine Daridon⁴, Jacques Felblinger^1,2, and Julien Oster^1,2

¹IADI, U1254, INSERM, Nancy, France, ²Université de Lorraine, Nancy, France, ³FHNW, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland, ⁴Metrolab Technology SA, Plan-les-Ouates, Switzerland

This paper presents a magnetic tracking method for the localization of a three-axis magnetometer within an MRI bore (Prisma, Siemens, Erlangen, Germany). The unique relationship between the Magnetic Gradient Fields (MGF) and the position within the bore allows locating the sensor through the use of a mapping of the MGF. This mapping is used for the training of a multi-layer perceptron neural network, which estimates the position of the sensor when measuring the MGF. Our technique was experimentally validated by moving the sensors within the MRI bore while playing a customized pulse sequence and by reconstructing the movements during post-processing.

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