Robotic surgery promises enhanced precision and adaptability over traditional surgical methods. It also offers the possibility of automating surgical interventions, resulting in reduced stress on the surgeon, better surgical outcomes, and lower costs. Cholecystectomy, the removal of the gallbladder, serves as an ideal model procedure for automation due to its distinct and well-contrasted anatomical features between the gallbladder and liver, along with standardized surgical maneuvers. Dissection is a frequently used subtask in cholecystectomy where the surgeon delivers the energy on the hook to detach the gallbladder from the liver. Hence, dissection along tissue boundaries is a good candidate for surgical automation. For the da Vinci surgical robot to perform the same procedure as a surgeon automatically, it needs to have the ability to (1) recognize and distinguish between the two different tissues (e.g. the liver and the gallbladder), (2) understand where the boundary between the two tissues is located in the 3D workspace, (3) locate the instrument tip relative to the boundary in the 3D space using visual feedback, and (4) move the instrument along the boundary. This paper presents a novel framework that addresses these challenges through AI-assisted image processing and vision-based robot control. We also present the ex-vivo evaluation of the automated procedure on chicken and pork liver specimens that demonstrates the effectiveness of the proposed framework.

翻译：机器人手术在精准性和适应性方面有望超越传统手术方法。它还能实现手术干预的自动化，从而减轻外科医生的压力、改善手术效果并降低成本。胆囊切除术（即切除胆囊）因其胆囊与肝脏之间具有清晰且对比鲜明的解剖特征，以及标准化的手术操作，成为自动化的理想模型手术。剥离是胆囊切除术中常用的子任务，医生通过电钩传递能量将胆囊从肝脏上分离。因此，沿组织边界的剥离是手术自动化的理想候选方案。为了令达芬奇手术机器人像外科医生一样自动执行该手术，它需要具备以下能力：（1）识别并区分两种不同组织（如肝脏和胆囊）；（2）理解两种组织边界在三维工作空间中的位置；（3）利用视觉反馈在三维空间中定位器械尖端相对于边界的位置；（4）沿边界移动器械。本文提出了一种新颖的框架，通过AI辅助图像处理和基于视觉的机器人控制解决了上述挑战。我们还展示了在鸡肝和猪肝样本上对该自动过程的离体评估，证明了所提框架的有效性。