基于实时切片到体积配准的机器人辅助甲状腺活检自主导航

doi:10.1007/s12204-023-2606-y

J Shanghai Jiaotong Univ Sci ›› 2023, Vol. 28 ›› Issue (3): 330-338.doi: 10.1007/s12204-023-2606-y

基于实时切片到体积配准的机器人辅助甲状腺活检自主导航

李坚¹，王星超¹，钟敏²，郑剑²，孙正隆¹

（1.香港中文大学理工学院，广东深圳 518172；2. 龙岗区人民医院，广东深圳 518172)

收稿日期:2022-10-30 修回日期:2023-02-08 接受日期:2023-05-28 出版日期:2023-05-28 发布日期:2023-05-22

Real-Time Slice-to-Volume Registration-Based Autonomous Navigation for Robot-Assisted Thyroid Biopsy

LI Jian1(李坚)，WANG Xingchao¹(王星超)，ZHONG Min^{2 (钟敏)，ZHENG Jian²(郑剑)，SUN Zhenglong^1*(孙正隆)}

(1. School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen 518172, Guangdong, China; 2. Longgang District People’s Hospital, Shenzhen 518172, Guangdong, China)

Received:2022-10-30 Revised:2023-02-08 Accepted:2023-05-28 Online:2023-05-28 Published:2023-05-22

摘要/Abstract

摘要： 随着医学成像和机器人技术的进步，完全自动诊断治疗的想法变得越来越有吸引力。超声检查具有无创、无辐射、成像速度快等特点，越来越多地被应用于临床，如妇产科、外科穿刺等。在本文中，我们提出了一种使用混合切片到体积配准方法的基于实时图像的视觉伺服控制方案。以这种方式，即使在存在干扰的情况下，机器人也可以根据术前计划自主将超声探头定位到所需的姿态。我们使用了甲状腺活检模体模型来设计和进行实验。结果表明，本文所提出的方案可以实现高达30 Hz的刷新率和（0.52±0.65）mm的跟踪精度。

关键词: 切片到体积配准，自主导航，甲状腺活检

Abstract: With advancements in medical imaging and robotic technology, the idea of fully autonomous diagnosis and treatment has become appealing, from ethereal to tangible. Owing to its characteristics of non-invasiveness, non-radiation, and fast imaging speed, ultrasonography has been increasingly used in clinical practice, such as in obstetrics, gynecology, and surgical puncture. In this paper, we propose a real-time image-based visual servo control scheme using a hybrid slice-to-volume registration method. In this manner, the robot can autonomously locate the ultrasound probe to the desired posture according to preoperational planning, even in the presence of disturbances. The experiments are designed and conducted using a thyroid biopsy phantom model. The results show that the proposed scheme can achieve a refresh rate of up to 30 Hz and a tracking accuracy of (0.52±0.65) mm.

Key words: slice-to-volume registration, autonomous navigation, thyroid biopsy

中图分类号:

TP 242

李坚1，王星超1，钟敏2，郑剑2，孙正隆1. 基于实时切片到体积配准的机器人辅助甲状腺活检自主导航[J]. J Shanghai Jiaotong Univ Sci, 2023, 28(3): 330-338.

LI Jian1 (李坚)，WANG Xingchao1 (王星超)，ZHONG Min2 (钟敏)，ZHENG Jian2(郑剑)，SUN Zhenglong1*(孙正隆). Real-Time Slice-to-Volume Registration-Based Autonomous Navigation for Robot-Assisted Thyroid Biopsy[J]. J Shanghai Jiaotong Univ Sci, 2023, 28(3): 330-338.

参考文献 31

[1]	CHAN V, PERLAS A. Basics of ultrasound imaging [M]//Atlas of ultrasound-guided procedures in interventional pain management. New York: Springer, 2011: 13-19.
[2]	HARRISON G, HARRIS A. Work-related musculoskeletal disorders in ultrasound: Can You reduce risk? [J]. Ultrasound, 2015, 23(4): 224-230.
[3]	MUIR M, HRYNKOW P, CHASE R, et al. The nature, cause, and extent of occupational musculoskeletal injuries among sonographers [J]. Journal of Diagnostic Medical Sonography, 2004, 20(5): 317-325.
[4]	DE OLIVEIRA FILHO G R. The construction of learning curves for basic skills in anesthetic procedures: An application for the cumulative sum method [J]. Anesthesia and Analgesia, 2002, 95(2): 411-416.
[5]	NING C P, JI X L, WANG H Q, et al. Association between the sonographer’s experience and diagnostic performance of IOTA simple rules [J]. World Journal of Surgical Oncology, 2018, 16(1): 1-7.
[6]	WANG H X, LI R, CHEN X, et al. Remote intelligent assisted diagnosis system for hepatic echinococcosis [M]//Medical ultrasound, and preterm, perinatal and paediatric image analysis. Cham: Springer International Publishing, 2020: 3-12.
[7]	HUANG Q H, LAN J L. Remote control of a robotic prosthesis arm with six-degree-of-freedom for ultrasonic scanning and three-dimensional imaging [J]. Biomedical Signal Processing and Control, 2019, 54: 101606.
[8]	SARTORI E, TADIELLO C, SECCHI C, et al. Teleechography using a two-layer teleoperation algorithm with energy scaling [C]//2019 International Conference on Robotics and Automation. Montreal: IEEE, 2019: 1569-1575.
[9]	MARCHAL M, TROCCAZ J. A one-DOF freehand haptic device for robotic tele-echography [J]. Studies in Health Technology and Informatics, 2004, 98: 231-233.
[10]	KAMINSKI J T, RAFATZAND K, ZHANG H K. Feasibility of robot-assisted ultrasound imaging with force feedback for assessment of thyroid diseases [J]. Proceedings of SPIE, 2020, 11315: 113151D.
[11]	NADEAU C, KRUPA A. Intensity-based ultrasound visual servoing: Modeling and validation with 2-D and 3-D probes [J]. IEEE Transactions on Robotics, 2013, 29(4): 1003-1015.
[12]	NAKADATE R, SOLIS J, TAKANISHI A, et al. Out-of-plane visual servoing method for tracking the carotid artery with a robot-assisted ultrasound diagnostic system [C]//2011 IEEE International Conference on Robotics and Automation. Shanghai: IEEE, 2011: 5267-5272.
[13]	HUANG Y W, XIAO W, WANG C Y, et al. Towards fully autonomous ultrasound scanning robot with imitation learning based on clinical protocols [J]. IEEE Robotics and Automation Letters, 2021, 6(2): 3671-3678.
[14]	KRUPA A, FOLIO D, NOVALES C, et al. Robotized tele-echography: An assisting visibility tool to support expert diagnostic [J]. IEEE Systems Journal, 2014, 10(3): 974-983.
[15]	JIANG Z L, DANIS N, BI Y, et al. Precise repositioning of robotic ultrasound: Improving registration-based motion compensation using ultrasound confidence optimization [J]. IEEE Transactions on Instrumentation and Measurement, 2022, 71: 1-11.
[16]	ZHANG S H, JIANG S, YANG Z Y, et al. An ultrasound image navigation robotic prostate brachytherapy system based on US to MRI deformable image registration method [J]. Hellenic Journal of Nuclear Medicine, 2016, 19(3): 223-230.
[17]	ZHANG S H, JIANG S, YANG Z Y, et al. 2D ultrasound and 3D MR image registration of the prostate for brachytherapy surgical navigation [J]. Medicine, 2015, 94(40): e1643.
[18]	ESTEBAN J, SIMSON W, WITZIG S R, et al. Robotic ultrasound-guided facet joint insertion [J]. International Journal of Computer Assisted Radiology and Surgery, 2018, 13(6): 895-904.
[19]	ZETTINIG O, FUERST B, KOJCEV R, et al. Toward real-time 3D ultrasound registration-based visual servoing for interventional navigation [C]//2016 IEEE International Conference on Robotics and Automation. Stockholm: IEEE, 2016: 945-950.
[20]	LASSO A, HEFFTER T, RANKIN A, et al. PLUS: Open-source toolkit for ultrasound-guided intervention systems [J]. IEEE Transactions on Biomedical Engineering, 2014, 61(10): 2527-2537.
[21]	RONNEBERGER O, FISCHER P, BROX T. U-Net: Convolutional networks for biomedical image segmentation [M]//Medical image computing and computer-assisted intervention – MICCAI 2015. Cham: Springer, 2015: 234-241.
[22]	WANG Q. GMM-based hidden markov random field for color image and 3D volume segmentation [DB/OL]. (2012-12-18). https://arxiv.org/abs/1212.4527
[23]	FERRANTE E, PARAGIOS N. Slice-to-volume medical image registration: A survey [J]. Medical Image Analysis, 2017, 39: 101-123.
[24]	MARAMI B, SIROUSPOUR S, CAPSON D W. Model-based 3D/2D deformable registration of MR images [C]//2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Boston: IEEE, 2011: 4880-4883.
[25]	MOCKUS J. The Bayesian approach to global optimization [M]//System modeling and optimization. Berlin/Heidelberg: Springer-Verlag, 2005: 473-481.
[26]	SRINIVAS N, KRAUSE A, KAKADE S M, et al. Gaussian process optimization in the bandit setting: No regret and experimental design [DB/OL]. (2009-12-21). https://arxiv.org/abs/0912.3995
[27]	NELDER J A, MEAD R. A simplex method for function minimization [J]. The Computer Journal, 1965, 7(4): 308-313.
[28]	CHAUMETTE F, HUTCHINSON S. Visual servo control. I. basic approaches [J]. IEEE Robotics & Automation Magazine, 2006, 13(4): 82-90.
[29]	MALIS E, CHAUMETTE F, BOUDET S. 2 1/2 D visual servoing [J]. IEEE Transactions on Robotics & Automation, 1999, 15(2): 238-250.
[30]	ALBU-SCHAFFER A, OTT C, FRESE U, et al. Cartesian impedance control of redundant robots: Recent results with the DLR-light-weight-arms [C]//2003 IEEE International Conference on Robotics and Automation. Taipei: IEEE, 2003: 3704-3709.
[31]	PRAGER R W, ROHLING R N, GEE A H, et al. Rapid calibration for 3-D freehand ultrasound [J]. Ultrasound in Medicine & Biology, 1998, 24(6): 855-869.

基于实时切片到体积配准的机器人辅助甲状腺活检自主导航

Real-Time Slice-to-Volume Registration-Based Autonomous Navigation for Robot-Assisted Thyroid Biopsy

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