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Global Registration of Ultrasound to MRI Using the LC2 Metric for Enabling Neurosurgical Guidance
Wolfgang Wein1, Alexander Ladikos1, Bernhard Fuerst2, Amit Shah2, Kanishka Sharma2, and Nassir Navab2
1ImFusion GmbH, München, Germany
2Computer Aided Medical Procedures, Technische Universität München, Germany
Abstract. Automatic and robust registration of pre-operative magnetic resonance imaging (MRI) and intra-operative ultrasound (US) is essential to neurosurgery. We reformulate and extend an approach which uses a Linear Correlation of Linear Combination (LC2)-based similarity metric, yielding a novel algorithm which allows for fully automatic US-MRI registration in the matter of seconds. It is invariant with respect to the unknown and locally varying relationship between US image intensities and both MRI intensity and its gradient. The overall method based on this both recovers global rigid alignment, as well as the parameters of a free-form-deformation (FFD) model. The algorithm is evaluated on 14 clinical neurosurgical cases with tumors, with an average landmark-based error of 2.52mm for the rigid transformation. In addition, we systematically study the accuracy, precision, and capture range of the algorithm, as well as its sensitivity to different choices of parameters.
LNCS 8149, p. 34 ff.
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© Springer-Verlag Berlin Heidelberg 2013