Ravigopal Sharan R, Sarma Achraj, Brumfiel Timothy A, Desai Jaydev P
Medical Robotics and Automation (RoboMed) Laboratory, Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332 USA.
IEEE Trans Med Robot Bionics. 2023 May;5(2):230-241. doi: 10.1109/tmrb.2023.3260273. Epub 2023 Mar 22.
Atherosclerosis is a medical condition that causes buildup of plaque in the blood vessels and narrowing of the arteries. Surgeons often treat this condition through angioplasty with catheter placements. Continuum guidewire robots offer significant advantages for catheter placements due to their dexterity. Tracking these guidewire robots and their surrounding workspace under fluoroscopy in real-time can be useful for visualization and accurate control. This paper discusses algorithms and methods to track the shape and orientation of the guidewire and the surrounding workspaces of phantom vasculatures in real-time under C-arm fluoroscopy. The shape of continuum guidewires is found through a semantic segmentation architecture based on MobileNetv2 with a Tversky loss function to deal with class imbalances. This shape is refined through medial axis filtering and parametric curve fitting to quantitatively describe the guidewire's pose. Using a constant curvature assumption for the guidewire's bending segments, the parameters that describe the joint variables are estimated in real-time for a tendon-actuated COaxially Aligned STeerable (COAST) guidewire robot and tracked through its traversal of an aortic bifurcation phantom. The accuracy of the tracking is ~90% and the execution times are within 100ms, and hence this method is deemed suitable for real-time tracking.
动脉粥样硬化是一种导致血管中斑块积聚和动脉狭窄的病症。外科医生通常通过放置导管的血管成形术来治疗这种病症。连续体导丝机器人因其灵活性,在导管放置方面具有显著优势。在荧光透视下实时跟踪这些导丝机器人及其周围工作空间,对于可视化和精确控制可能很有用。本文讨论了在C型臂荧光透视下实时跟踪导丝形状和方向以及虚拟脉管系统周围工作空间的算法和方法。通过基于MobileNetv2的语义分割架构和Tversky损失函数来处理类别不平衡,从而找到连续体导丝的形状。通过中轴线滤波和参数曲线拟合对该形状进行细化,以定量描述导丝的姿态。对于肌腱驱动的同轴对齐可转向(COAST)导丝机器人,利用导丝弯曲段的恒定曲率假设,实时估计描述关节变量的参数,并通过其在主动脉分叉模型中的穿行进行跟踪。跟踪精度约为90%,执行时间在100毫秒以内,因此该方法被认为适用于实时跟踪。