Cone-Beam CT (CBCT) is a valuable imaging modality for the intraoperative localization of pulmonary nodules during Video-Assisted Thoracoscopic Surgery (VATS). However, inferring the nodule position from the CBCT to the operative field remains challenging and could greatly benefit from computer-aided guiding. As a first step towards an Augmented Endoscopy guiding system, we propose to register 2D monocular endoscopic views into the 3D CBCT space. Ribs and wound protectors are segmented in both imaging modalities, then registered using an image-to-cloud Iterative Closest Point variant. The method is evaluated qualitatively on clinical VATS video sequences from 3 patients. The promising results validate this first step towards a seamless monocular VATS navigation.
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