Lerotic Mirna, Chung Adrian J, Mylonas George, Yang Guang-Zhong
Institute of Biomedical Engineering, Imperial College, London SW7 2AZ, UK.
Med Image Comput Comput Assist Interv. 2007;10(Pt 2):102-9. doi: 10.1007/978-3-540-75759-7_13.
The increasing use of robotic assisted minimally invasive surgery (MIS) provides an ideal environment for using Augmented Reality (AR) for performing image guided surgery. Seamless synthesis of AR depends on a number of factors relating to the way in which virtual objects appear and visually interact with a real environment. Traditional overlaid AR approaches generally suffer from a loss of depth perception. This paper presents a new AR method for robotic assisted MIS, which uses a novel pq-space based non-photorealistic rendering technique for providing see-through vision of the embedded virtual object whilst maintaining salient anatomical details of the exposed anatomical surface. Experimental results with both phantom and in vivo lung lobectomy data demonstrate the visual realism achieved for the proposed method and its accuracy in providing high fidelity AR depth perception.
机器人辅助微创手术(MIS)的使用日益增加,为利用增强现实(AR)进行图像引导手术提供了理想环境。AR的无缝合成取决于与虚拟物体呈现方式以及与真实环境视觉交互方式相关的多个因素。传统的叠加式AR方法通常存在深度感知丧失的问题。本文提出了一种用于机器人辅助MIS的新AR方法,该方法使用基于pq空间的新型非真实感渲染技术,以提供嵌入式虚拟物体的透视视觉,同时保持暴露解剖表面的显著解剖细节。对模拟数据和体内肺叶切除术数据的实验结果表明了该方法所实现的视觉真实感及其在提供高保真AR深度感知方面的准确性。
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