Tip estimation approach for concentric tube robots using 2D ultrasound images and kinematic model.

Journal: Medical & biological engineering & computing
Published Date:

Abstract

Concentric tube robot (CTR) is an efficient approach for minimally invasive surgery (MIS) and diagnosis due to its small size and high dexterity. To manipulate the robot accurately and safely inside the human body, tip position and shape information need to be well measured. In this paper, we propose a tip estimation method based on 2D ultrasound images with the help of the forward kinematic model of CTR. The forward kinematic model can help to provide a fast ultrasound scanning path and narrow the region of interest in ultrasound images. For each tube, only three scan positions are needed by combining the kinematic model prediction as prior knowledge. After that, the curve fitting method is used for its shape reconstruction, while its tip position can be estimated based on the constraints of its structure and length.7 This method provides the advantage that only three scan positions are needed for estimating the tip of each telescoping section. Moreover, no structure modification is needed on the robot, which makes it an appropriate approach for existing flexible surgical robots. Experimental results verified the feasibility of the proposed method and the tip estimation error is 0.59 mm. Graphical abstract In this paper, we propose a tip estimation method based on 2D Ultrasound images with the help of the forward kinematic model of CTR. The forward kinematic model can help to provide a fast Ultrasound scanning path and narrow the region of interest in Ultrasound images. For each tube, only three scan positions are needed by combining the kinematic model prediction as prior knowledge. After that, the curve fitting method is used for its shape reconstruction, while its tip position can be estimated based on the constraints of its structure and length.

Authors

  • Zihao Li
    School of Mechanical Engineering and Automation, Harbin Institute of Technology(Shenzhen), Shenzhen, 518055, China.
  • Xing Yang
  • Shuang Song
    Department of Ophthalmology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Li Liu
    Metanotitia Inc., Shenzhen, China.
  • Max Q-H Meng
    The Chinese University of Hong Kong, Shatin, Hong Kong.