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Toward Autonomous Robotic Micro-Suturing using Optical Coherence Tomography Calibration and Path Planning

Yuan Tian, Mark Draelos, Gao Tang, Ruobing Qian, Anthony N. Kuo, Joseph A. Izatt, Kris Hauser

Year
2020
Citations
3
Access
Open access

Abstract

Robotic automation has the potential to assist human surgeons in performing suturing tasks in microsurgery, and in order to do so a robot must be able to guide a needle with sub-millimeter precision through soft tissue. This paper presents a robotic suturing system that uses 3D optical coherence tomography (OCT) system for imaging feedback. Calibration of the robot-OCT and robot-needle transforms, wound detection, keypoint identification, and path planning are all performed automatically. The calibration method handles pose uncertainty when the needle is grasped using a variant of iterative closest points. The path planner uses the identified wound shape to calculate needle entry and exit points to yield an evenly-matched wound shape after closure. Experiments on tissue phantoms and animal tissue demonstrate that the system can pass a suture needle through wounds with 0.27 mm overall accuracy in achieving the planned entry and exit points.

Keywords

Optical coherence tomographyComputer visionArtificial intelligenceComputer scienceCalibrationRobotMotion planningAutomationCoherence (philosophical gambling strategy)Biomedical engineering

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