A model-based registration approach of preoperative MRI with 3D ultrasound of the liver for Interventional guidance procedures
Samuel Kadoury, Lyubomir Zagorchev, Bradford J. Wood, Aradhana M. Venkatesan, Juergen Weese, James R. Jago, Jochen Kruecker · 2012
In this paper, we present a novel approach to rigidly register intraoperative electromagnetically tracked ultrasound (US) with pre-operative contrast-enhanced magnetic resonance (MR) images. The clinical rationale for this work is to allow accurate needle placement during thermal ablations of liver metastases using multimodal imaging. We adopt a model-based approach that rigidly matches segmented liver surface shapes obtained from the multimodal image volumes. Towards this end, a shape-constrained deformable surface model combining the strengths of both deformable and active shape models is used to segment the liver surface from the MR scan. It incorporates a priori shape information while external forces guide the deformation and adapts the model to a target structure. The liver boundary is extracted from US by merging a dynamic region-growing method with a graph-based segmentation framework anchored on adaptive priors of neighboring surface points. Registration is performed with a weighted ICP algorithm with a physiological penalizing term. The MR segmentation model was trained with 30 datasets and validated on a separate cohort of 10 patients with corresponding ground truth. The accuracy and robustness of the method were assessed by registering four US/MR datasets, yielding accurate landmark registration errors (3.7 ± 0.69mm) and high robustness, and is thus acceptable for radiofrequency clinical applications.