论文标题
Tatoo:基于视觉的关节跟踪解剖结构和颅底手术工具
TAToo: Vision-based Joint Tracking of Anatomy and Tool for Skull-base Surgery
论文作者
论文摘要
目的:跟踪手术工具的3D运动和患者解剖结构是计算机辅助的头骨基础手术的基本要求。估计的运动既可以用于术中指导和下游技能分析。仅从外科视频中恢复这种运动是可取的,因为它符合当前的临床工作流程和仪器。 方法:我们介绍解剖学和工具的跟踪器(tatoo)。塔图(Tatoo)共同跟踪来自立体微观视频的患者头骨和外科手术钻的刚性3D运动。 Tatoo通过迭代优化过程以端到端可区分形式估算运动。对于稳健的跟踪性能,Tatoo采用了概率公式,并在对象级别上执行几何约束。 结果:我们在两个模拟数据上验证了tatoo,其中可用地面真相运动以及拟人化的幻象数据,其中光学跟踪提供了强大的基线。我们分别报告了头骨和钻头的次数和毫米框架间跟踪精度,旋转误差低于1°。我们进一步说明了如何在手术导航设置中使用塔图。 结论:我们提出了Tatoo,同时跟踪外科手术工具和颅底手术中的患者解剖结构。 Tatoo直接预测手术视频的运动,而无需任何标记。我们的结果表明,塔图的性能与竞争方法相比有利。未来的工作将包括对我们的深度网络进行微观调整,以达到所需的1毫米临床精度目标,以便在颅骨基础中进行手术应用。
Purpose: Tracking the 3D motion of the surgical tool and the patient anatomy is a fundamental requirement for computer-assisted skull-base surgery. The estimated motion can be used both for intra-operative guidance and for downstream skill analysis. Recovering such motion solely from surgical videos is desirable, as it is compliant with current clinical workflows and instrumentation. Methods: We present Tracker of Anatomy and Tool (TAToo). TAToo jointly tracks the rigid 3D motion of patient skull and surgical drill from stereo microscopic videos. TAToo estimates motion via an iterative optimization process in an end-to-end differentiable form. For robust tracking performance, TAToo adopts a probabilistic formulation and enforces geometric constraints on the object level. Results: We validate TAToo on both simulation data, where ground truth motion is available, as well as on anthropomorphic phantom data, where optical tracking provides a strong baseline. We report sub-millimeter and millimeter inter-frame tracking accuracy for skull and drill, respectively, with rotation errors below 1°. We further illustrate how TAToo may be used in a surgical navigation setting. Conclusion: We present TAToo, which simultaneously tracks the surgical tool and the patient anatomy in skull-base surgery. TAToo directly predicts the motion from surgical videos, without the need of any markers. Our results show that the performance of TAToo compares favorably to competing approaches. Future work will include fine-tuning of our depth network to reach a 1 mm clinical accuracy goal desired for surgical applications in the skull base.