Global Registration of Ultrasound to MRI Using the LC2 Metric for Enabling Neurosurgical Guidance

Abstract. Automatic and robust registration of pre-operative magnetic resonance imaging (MRI) and intra-operative ultrasound (US) is essen-tial to neurosurgery. We reformulate and extend an approach which uses a Linear Correlation of Linear Combination (LC2)-based similarity met-ric, 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 systemat-ically study the accuracy, precision, and capture range of the algorithm, as well as its sensitivity to different choices of parameters.