Model-based 2D-3D registration and tracking of deformable objects for image-guided minimally invasive cardiac interventions

在过去的十年里，由于技术的进步，心脏手术的面貌发生了变化。其中一项进步是微创心脏手术的发展，该手术通过小切口（关键孔手术）进行，而不是通过传统的开胸手术。使用这种技术，小型内窥镜相机和专门的仪器通过小的人工切口插入。对于病人来说，这减少了发病率，并导致手术后更快，更少痛苦的恢复。然而，对于外科医生来说，这带来了许多问题，如有限的触觉反馈和有限的视觉反馈。本课题的目的是利用手术机器人开发一种图像引导的微创心脏手术系统。在这个项目中，我们将追求的关键研究问题是开发新的基于模型的2D-3D配准技术，用于将3D可变形物体（如心脏和血管）与2D内窥镜视频图像匹配。这种注册将使我们能够建立外科医生看到的二维内窥镜视频图像与患者解剖结构之间的关系。我们建议将来自术前图像数据的模型叠加到实时二维内窥镜视频图像上。这将允许外科医生利用术前断层扫描数据在手术过程中精确定位和跟踪目标。

In the past decade, the face of cardiac surgery has been changed by a number of technologic advances. One such advance is the development of minimally invasive cardiac surgery where the surgical intervention is done through small incisions ( key hole surgery ) rather than through conventional open chest surgery. With this technique, small endoscopic cameras and specialized instruments are inserted through small artificial incisions. For the patient this reduces morbidity and leads to faster, less painful recovery from surgery. However, for the surgeon this poses a number of problems such as the limited tactile feedback and restricted visual feedback.The purpose of this project is to develop a image-guided minimally invasive cardiac surgery system using a surgical robot. The key research issue which we will pursue in this project is the development of novel model-based 2D-3D registration techniques for matching 3D deformable objects such as the heart as well as vessels to 2D endoscopic video images. This registration will enable us to establish the relationship between the 2D endoscopic video images seen by the surgeon and the patient's anatomy. We propose to superimpose models derived from preoperative image data onto the live 2D endoscopic video images. This will allow the surgeon to utilise preoperative tomographic data to accurate localise and track targets during the operation.