IHU, Institut Hospitalo-Universitaire, Strasbourg, France; ICube (UMR 7357 CNRS), Université de Strasbourg, France.
Virtual Surg, IRCAD, Strasbourg, France.
Med Image Anal. 2016 May;30:130-143. doi: 10.1016/j.media.2016.01.008. Epub 2016 Feb 13.
The use of augmented reality in minimally invasive surgery has been the subject of much research for more than a decade. The endoscopic view of the surgical scene is typically augmented with a 3D model extracted from a preoperative acquisition. However, the organs of interest often present major changes in shape and location because of the pneumoperitoneum and patient displacement. There have been numerous attempts to compensate for this distortion between the pre- and intraoperative states. Some have attempted to recover the visible surface of the organ through image analysis and register it to the preoperative data, but this has proven insufficiently robust and may be problematic with large organs. A second approach is to introduce an intraoperative 3D imaging system as a transition. Hybrid operating rooms are becoming more and more popular, so this seems to be a viable solution, but current techniques require yet another external and constraining piece of apparatus such as an optical tracking system to determine the relationship between the intraoperative images and the endoscopic view. In this article, we propose a new approach to automatically register the reconstruction from an intraoperative CT acquisition with the static endoscopic view, by locating the endoscope tip in the volume data. We first describe our method to localize the endoscope orientation in the intraoperative image using standard image processing algorithms. Secondly, we highlight that the axis of the endoscope needs a specific calibration process to ensure proper registration accuracy. In the last section, we present quantitative and qualitative results proving the feasibility and the clinical potential of our approach.
增强现实技术在微创手术中的应用已经成为十多年来的研究热点。手术场景的内窥镜视图通常通过从术前采集提取的 3D 模型进行增强。然而,由于气腹和患者移位,感兴趣的器官的形状和位置经常发生重大变化。已经有许多尝试来补偿这种术前和术中状态之间的失真。有些人试图通过图像分析恢复器官的可见表面,并将其注册到术前数据,但事实证明这不够稳健,并且对于大型器官可能存在问题。第二种方法是引入术中 3D 成像系统作为过渡。杂交手术室越来越受欢迎,因此这似乎是一种可行的解决方案,但当前的技术需要另一个外部和约束性的设备,例如光学跟踪系统,以确定术中图像与内窥镜视图之间的关系。在本文中,我们提出了一种新的方法,通过在体数据中定位内窥镜尖端,自动将术中 CT 采集的重建与静态内窥镜视图进行配准。我们首先描述了我们使用标准图像处理算法在术中图像中定位内窥镜方向的方法。其次,我们强调了内窥镜轴需要特定的校准过程,以确保适当的配准精度。在最后一节中,我们展示了定量和定性结果,证明了我们的方法的可行性和临床潜力。