Abstract
Patellofemoral joint (PFJ) issues affect one in four people, with 20% experiencing chronic knee pain despite treatment. Poor outcomes and pain after knee replacement surgery are often linked to patellar mal-tracking. Traditional imaging methods like CT and MRI face challenges, including cost and metal artefacts, and there's currently no ideal way to observe joint motion without issues such as soft tissue artefacts or radiation exposure. A new system to monitor joint motion could significantly improve understanding of PFJ dynamics, aiding in better patient care and outcomes. Combining 2D ultrasound with motion tracking for 3D reconstruction of the joint using semantic segmentation and position registration can be a solution. However, the need for expensive external infrastructure to estimate the trajectories of the scanner remains the main limitation to implementing 3D bone reconstruction from handheld ultrasound scanning clinically. We proposed the Visual-Inertial Odometry (VIO) and the deep learning-based inertial-only odometry methods as alternatives to motion capture for tracking a handheld ultrasound scanner. The 3D reconstruction generated by these methods has demonstrated potential for assessing the PFJ and for further measurements from free-hand ultrasound scans. The results show that the VIO method performs as well as the motion capture method, with average reconstruction errors of 1.25 mm and 1.21 mm, respectively. The VIO method is the first infrastructure-free method for 3D reconstruction of bone from wireless handheld ultrasound scanning with an accuracy comparable to methods that require external infrastructure.
Abstract (translated)
翻译：Patellofemoral joint (PFJ) 问题影响四分之一的人，即使经过治疗，20%的人仍然会经历慢性膝盖疼痛。腿部置换手术后的不良结果和疼痛通常与膝关节不良运动有关。传统的影像技术如 CT 和 MRI 面临成本和金属伪影等挑战，目前没有理想的方法在没有软组织伪影或辐射暴露等问题的情况下观察关节运动。一种新系统监测关节运动可能显著改善对 PFJ 动态的理解，有助于提高患者护理和治疗效果。将 2D 超声与运动跟踪结合进行关节三维重建可以使用语义分割和位置配准，可能是解决方案。然而，需要昂贵的外部基础设施估计扫描器的轨迹仍然是实施临床超声三维骨重建的主要限制。我们提出了视觉惯性测量 (VIO) 和基于深度学习的惯性仅运动跟踪方法作为手持超声扫描器的运动捕捉替代方法。这些方法产生的 3D 重建已经证明了评估 PFJ 的潜力和从自由手超声扫描中进行进一步测量的可能性。结果表明，VIO 方法与运动捕捉方法的表现相同，平均重建误差分别为 1.25 mm 和 1.21 mm。VIO 方法是第一个无基础设施免费的 3D 骨重建方法，其准确性相当于需要外部基础设施的方法。
URL
https://arxiv.org/abs/2404.15847
