Robot-Assisted Deep Venous Thrombosis Ultrasound Examination Using Virtual Fixture

被引:6
作者
Huang, Dianye [1 ]
Yang, Chenguang [2 ]
Zhou, Mingchuan [3 ]
Karlas, Angelos [4 ,5 ,6 ,7 ]
Navab, Nassir [1 ]
Jiang, Zhongliang [1 ]
机构
[1] Tech Univ Munich, Sch Computat Informat & Technol, Chair Comp Aided Med Procedures & Augmented Real, D-85748 Garching, Germany
[2] Univ West England, Bristol Robot Lab, Bristol BS16 1QY, Avon, England
[3] Zhejiang Univ, Coll Biosyst Engn & Food Sci, Hangzhou 310058, Peoples R China
[4] Helmholtz Zentrum Munchen, Inst Biol & Med Imaging, D-85764 Neuherberg, Germany
[5] Tech Univ Munich, Sch Med, Cent Inst Translat Canc Res TranslaTUM, D-81675 Munich, Germany
[6] Tech Univ Munich, Klinikum Rechts Isar, Dept Vasc & Endovasc Surg, D-80333 Munich, Germany
[7] German Ctr Cardiovasc Res DZHK, Partner Site Munich Heart Alliance, D-80636 Munich, Germany
关键词
Robots; Force; Probes; Fixtures; Cameras; Veins; Thrombosis; Deep venous thrombosis (DVT); robotic ultrasound; hybrid force motion control; virtual fixture; path planning; SYSTEM;
D O I
10.1109/TASE.2024.3351076
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Deep Venous Thrombosis (DVT) is a common vascular disease with blood clots inside deep veins, which may block blood flow or even cause a life-threatening pulmonary embolism. A typical exam for DVT using ultrasound (US) imaging is by pressing the target vein until its lumen is fully compressed. However, the compression exam is highly operator-dependent. To alleviate intra- and inter-variations, we present a robotic US system with a novel hybrid force motion control scheme ensuring position and force tracking accuracy, and soft landing of the probe onto the target surface. In addition, a path-based virtual fixture is proposed to realize easy human-robot interaction for repeat compression operation at the lesion location. To ensure the biometric measurements obtained in different examinations are comparable, the 6D scanning path is determined in a coarse-to-fine manner using both an external RGBD camera and US images. The RGBD camera is first used to extract a rough scanning path on the object. Then, the segmented vascular lumen from US images are used to optimize the scanning path to ensure the visibility of the target object. To generate a continuous scan path for developing virtual fixtures, an arc-length based path fitting model considering both position and orientation is proposed. Finally, the whole system is evaluated on a human-like arm phantom with an uneven surface. The code (https://github.com/dianyeHuang/RobDVTUS) and intuitive demonstration video (https://www.youtube.com/watch?v=3xFyqU1rV8c) can be publicly accessed.
引用
收藏
页码:381 / 392
页数:12
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