In the field of image-guided liver surgery (IGLS), the initial registration of the intra-operative organ surface with preoperative tomographic image data is performed on manually selected anatomical landmarks. In this paper, we introduce a fully automatic scheme that is able to estimate the transformation for initial organ registration in a multi-modal setup aligning intra-operative time-of-flight (ToF) with preoperative computed tomography (CT) data, without manual interaction. The method consists of three stages: First, we extract geometric features that encode the local surface topology in a discriminative manner based on a novel gradient operator. Second, based on these features, point correspondences are established and deployed for estimating a coarse initial transformation. Third, we apply a conventional iterative closest point (ICP) algorithm to refine the alignment. The proposed method was evaluated for an open abdominal hepatic surgery scenario with invitro experiments on four porcine livers. The method achieved a mean distance of 4.82 ± 0.79 mm and 1.70 ± 0.36 mm for the coarse and fine registration, respectively.
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