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Abstract. The reconstruction of three-dimensional (3D) ultrasound panorama from multiple ultrasound volumes can provide a wide field of view for better clinical diagnosis. Registration of ultrasound volumes has been a key issue for the success of this panoramic process. In this paper, we propose a method to register and stitch ultrasound volumes, which are scanned by dedicated ultrasound probe, based on an improved 3D Scale Invariant Feature Transform (SIFT) algorithm. We propose methods to exclude artifacts from ultrasound images in order to improve the overall performance in 3D feature point extraction and matching. Our method has been validated on both phantom and clinical data sets of human liver. Experimental results show the effectiveness and stability of our approach, and the precision of our method is comparable to that of the position tracker based registration.

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Virtual reality based learning of human anatomy is feasible when a database of 3D organ models is available for the learner to explore, visualize, and dissect in virtual space interactively. In this article, we present our latest work on photorealistic virtual anatomy applications based on the Chinese Visible Human (CVH) data. We have focused on the development of state-of-the-art virtual environments that feature interactive photo-realistic visualization and dissection of virtual anatomical models constructed from ultra-high resolution CVH datasets. We also outline our latest progress in applying these highly accurate virtual and functional organ models to generate realistic look and feel to advanced surgical simulators.