Trocar tracking using deep learning for teleoperated microsurgery robots in vitreoretinal surgery = 유리체 절제술 수행용 원격조종 미세수술로봇을 위한 딥러닝 기반 트로카 추적

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Vitreoretinal surgery represents a medical procedure whose tasks exist on the edge of human capability, given the relative scale of possible human hand movements, and afflicted areas on the retina. Performing vitreoretinal surgery using teleoperated robots, as opposed to manually, can potentially greatly reduce the difficulty level and required skill, and minimize the risk for the patient. However, the method employed by existing microsurgery robots for computing the remote centre of motion (RCM) of their surgical tool depends on a spherical eye model which is insufficiently accurate. In this thesis, a safety concern associated with inaccurate RCM placement is shown. A computer vision-based system is proposed which can provide an accurate, model-free RCM placement, as well as enable automatic microscope positioning. A camera is added to a microsurgery robot and the video feed is segmented to locate the iris and trocars in real time in 2-D using a convolutional neural network (CNN). The computed trocar positions are used in tandem with information provided by the robot’s encoders to place the 3-D position of the slave robot’s RCM. The iris position can be used to align the iris with the microscope automatically, to provide the view of the workspace inside the eye. The system’s accuracy is validated in a dry-lab experiment.
Advisors
Kwon, Dong-Sooresearcher권동수researcher
Description
한국과학기술원 :로봇공학학제전공,
Publisher
한국과학기술원
Issue Date
2020
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 로봇공학학제전공, 2020.8,[39 p. :]

Keywords

Vitreoretinal surgery▼amicrosurgery robot▼amaster-slave▼aRCM▼aComputer vision▼asemantic segmentation▼aCNN; 수녀원 신경망▼a미세 수술▼a원격 조종 로봇▼aRCM▼a자궁내막수술▼a컴퓨터 시각

URI
http://hdl.handle.net/10203/284964
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=925123&flag=dissertation
Appears in Collection
RE-Theses_Master(석사논문)
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