Totz Johannes, Mountney Peter, Stoyanov Danail, Yang Guang-Zhong
The Hamlyn Centre for Robotic Surgery, Imperial College London, UK.
Med Image Comput Comput Assist Interv. 2011;14(Pt 1):89-96. doi: 10.1007/978-3-642-23623-5_12.
Recent introduction of dynamic view expansion has led to the development of computer vision methods for minimally invasive surgery to artificially expand the intra-operative field-of-view of the laparoscope. This provides improved awareness of the surrounding anatomical structures and minimises the effect of disorientation during surgical navigation. It permits the augmentation of live laparoscope images with information from previously captured views. Current approaches, however, can only represent the tissue geometry as planar surfaces or sparse 3D models, thus introducing noticeable visual artefacts in the final rendering results. This paper proposes a high-fidelity tissue geometry mapping by combining a sparse SLAM map with semi-dense surface reconstruction. The method is validated on phantom data with known ground truth, as well as in-vivo data captured during a robotic assisted MIS procedure. The derived results have shown that the method is able to effectively increase the coverage of the expanded surgical view without compromising mapping accuracy.
动态视野扩展技术的近期引入推动了用于微创手术的计算机视觉方法的发展，以人工扩展腹腔镜的术中视野。这提高了对周围解剖结构的认知，并在手术导航过程中最大限度地减少了迷失方向的影响。它允许用先前捕获视图中的信息增强实时腹腔镜图像。然而，当前的方法只能将组织几何形状表示为平面表面或稀疏的3D模型，从而在最终渲染结果中引入明显的视觉伪影。本文提出了一种通过将稀疏同步定位与地图构建（SLAM）地图与半密集表面重建相结合的高保真组织几何映射方法。该方法在具有已知地面真值的体模数据以及机器人辅助微创手术过程中捕获的体内数据上得到了验证。所得结果表明，该方法能够有效增加扩展手术视野的覆盖范围，同时不影响映射精度。
