Non-linear approach for MRI to intra-operative US registration using structural skeleton

Abstract

Gliomas are primary brain tumors of central nervous system. Appropriate resection of gliomas in the early tumor stage is known to increase survival rate. However, the accurate resection of tumor is a challenging problem because the soft tissue shift may occur during the operation. To provide proper guidance to neurosurgery, it is necessary to align magnetic resonance imaging (MRI) and intra-operative ultrasound (iUS). In previous studies, many algorithms tried to find fiducial points that can lead to the appropriate registration. But these methods required manual specifications from experts to ensure the reliability of the fiducials. In this study, we proposed a data-driven approach for MRI-iUS non-linear registration using structural skeletons. The visualization of our results indicated that our approach might provide better registration performance.