Hu Mingxing, Penney Graeme, Edwards Philip, Figl Michael, Hawkes David
Centre for Medical Image Computing, University College London.
Med Image Comput Comput Assist Interv. 2007;10(Pt 1):68-77. doi: 10.1007/978-3-540-75757-3_9.
While Minimally Invasive Surgery (MIS) offers great benefits to patients compared with open surgery surgeons suffer from a restricted field-of-view and obstruction from instruments. We present a novel method for 3D reconstruction of soft tissue, which can provide a wider field-of-view with 3D information for surgeons, including restoration of missing data. The paper focuses on the use of Structure from Motion (SFM) techniques to solve the missing data problem and application of competitive evolutionary agents to improve the robustness to missing data and outliers. The method has been evaluated with synthetic data, images from a phantom heart model, and in vivo MIS image sequences using the da Vinci telerobotic surgical system.
虽然与开放手术相比,微创手术(MIS)为患者带来了巨大益处,但外科医生面临视野受限和器械遮挡的问题。我们提出了一种软组织三维重建的新方法,该方法可为外科医生提供包含缺失数据恢复的更广阔视野的三维信息。本文重点介绍了利用运动结构(SFM)技术解决缺失数据问题,以及应用竞争性进化智能体提高对缺失数据和异常值的鲁棒性。该方法已通过合成数据、来自模拟心脏模型的图像以及使用达芬奇远程机器人手术系统的体内MIS图像序列进行了评估。