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Comparison of 3D Surgical Tool Segmentation Procedures with Robot Kinematics Prior

机译:3D手术工具分割程序与机器人运动学先验的比较

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3D reconstruction and surgical tool segmentation are necessary for several advanced tasks in robot-assisted laparoscopic surgery. These tasks include vision-based force estimation, surgical guidance, and medical image registration where pre-operative data (CT or MRI scan image slices) are overlaid on patient anatomy in real-time during surgery [1] to name a few. In this work, two main strategies were considered: (1) initialize with surgical tool segmentation from 2D images, then proceed to local 3D reconstruction near the tool-tissue interaction region by projecting the segmented result into 3D space, and (2) initialize with 3D reconstruction of the entire surgical task space, followed by surgical tool segmentation from within the 3D reconstructed model. Both methods were implemented on the Raven II surgical robot system, and accuracy and time complexity for both methods were comparatively analyzed while considering various task parameters. Finally, based on the results of this work, guidelines for selecting reconstruction and segmentation strategies and procedure for particular situations are outlined in Section V.
机译:在机器人辅助腹腔镜手术中的几种高级任务是必要的3D重建和外科刀具分割。这些任务包括基于视觉的力估计,外科指导和医学图像登记,其中预先操作系统(CT或MRI扫描图像切片)在手术期间实时地覆盖在患者解剖学上[1]以命名几个。在这项工作中,考虑了两个主要策略:(1)通过2D图像与外科手术工具分段初始化,然后通过将分段结果投射到3D空间来进行刀具组合交互区域附近的本地3D重建,(2)初始化3D重建整个外科任务空间,随后是3D重建模型中的外科刀具分割。两种方法都在乌鸦II外科机器人系统上实施,并且在考虑各种任务参数的同时对两种方法的准确性和时间复杂性进行了比较。最后,根据这项工作的结果,第五节中概述了选择重建和细分策略和程序的准则。

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