AI 中文总结
ProCut提出一种完全可微分的概率切割拓扑框架，利用连续sigmoid公式和SVGD推断，实现软组织切割过程中的拓扑变化估计，并开发自主解剖算法，在模拟和真实电外科环境中显著提升拓扑估计准确性和解剖精度。
AI 中文摘要
准确建模和跟踪软组织的变形对于广泛的介入和外科手术至关重要。然而，当前方法在涉及拓扑变化（如切割和解剖）的场景中面临挑战，这是由于连接性的显式变化所引入的固有非线性和不连续性。在这项工作中，我们提出了一种新颖的、完全可微分的框架，能够在可变形跟踪过程中对拓扑变化进行稳健的估计和建模。我们的方法引入了一种基于连续sigmoid函数的公式，以平滑原本离散的组织切割事件，使其适用于基于梯度的优化，在可微分的基于位置的动力学（PBD）模拟中进行。为了考虑不确定性并在存在噪声视觉数据的情况下提高稳健性，我们结合了Stein变分梯度下降（SVGD）进行基于粒子的概率推断，为拓扑状态估计生成多个假设。在此基础上，我们开发了一种针对薄壳组织的自主解剖算法，利用拓扑更新来指导闭环切割轨迹控制。我们在模拟和真实电外科环境中评估了我们的方法，证明了在拓扑估计准确性和解剖精度方面相较于现有方法的显著改进。我们的结果突显了该框架在软组织外科手术中推进自动化的潜力，通过在复杂结构变化存在的情况下实现可靠的感知和控制。
英文摘要
Accurately modeling and tracking the deformation of soft tissue is critical for a wide range of interventional and surgical procedures. However, current methods struggle in scenarios involving topological changes, such as cutting and dissection, due to the inherent non-linearity and discontinuity introduced by explicit changes in connectivity. In this work, we present a novel, fully differentiable framework that enables robust estimation and modeling of topological changes during deformable tracking. Our method introduces a continuous, sigmoid-based formulation to smooth the otherwise discrete event of tissue cutting, making it amenable to gradient-based optimization within a differentiable Position-Based Dynamics (PBD) simulation. To account for uncertainty and improve robustness in the presence of noisy visual data, we incorporate Stein Variational Gradient Descent (SVGD) for particle-based probabilistic inference, generating multiple hypotheses for topological state estimation. Building on this foundation, we develop an autonomous dissection algorithm for thin-shell tissues that leverages topological updates to guide closed-loop cutting trajectory control. We evaluate our approach in both simulated and real-world electrosurgical environments, demonstrating significant improvements in topological estimation accuracy and dissection precision over existing methods. Our results highlight the potential of this framework to advance automation in soft-tissue surgical procedures by enabling reliable perception and control in the presence of complex structural changes.
