Vision Based Surgical Tool Tracking with Robot Kinematics Prior
| dc.contributor.advisor | Hannaford, Blake | |
| dc.contributor.author | Su, Yun-Hsuan | |
| dc.date.accessioned | 2017-10-26T20:49:20Z | |
| dc.date.available | 2017-10-26T20:49:20Z | |
| dc.date.issued | 2017-10-26 | |
| dc.date.submitted | 2017-08 | |
| dc.description | Thesis (Master's)--University of Washington, 2017-08 | |
| dc.description.abstract | Robot assisted minimally invasive surgery combines the skill and techniques of highly-trained surgeons with the robustness and precision of machines. Through a teleoperation scheme, surgeons can execute high-level surgical tasks by commanding instruments controlled by precise robotic devices. Several advantages arise. To name a few: (1) achieved precision is beyond that of human dexterity alone (2) a greater number of kinematic degrees of freedom are possible at the surgical tool tip (3) surgeons are able to operate remotely, i.e. agnostic of patient location given a suitable communication line. Despite the numerous advantages over traditional key-hole or laparoscopic surgery, the lack of realistic and real-time force feedback is a major drawback --- discerning tool-tissue interactions can be unintuitive and can ultimately result in unintentional tissue damage. Directly sensing forces at the tool-tissue interface is theoretically possible using tool tip mounted force sensors, but this approach is not amenable to required sterilization procedures. Thus, a vision based force estimation method is proposed to infer the applied force based on real-time analysis of tissue deformation. | |
| dc.embargo.terms | Open Access | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.other | Su_washington_0250O_17733.pdf | |
| dc.identifier.uri | http://hdl.handle.net/1773/40548 | |
| dc.language.iso | en_US | |
| dc.relation.haspart | First stage result.mp4; video; Demo video for first stage: image segmentation. | |
| dc.relation.haspart | slide.pptx; presentation; This is the slide for my MS thesis defense. | |
| dc.relation.haspart | Produce.wmv; video; Demo video for second stage: depth rendering. | |
| dc.rights | CC BY | |
| dc.subject | Image Segmentation | |
| dc.subject | Raven Surgical Robot | |
| dc.subject | Surgical Instrument Tracking | |
| dc.subject | Surgical Robotics | |
| dc.subject | Engineering | |
| dc.subject.other | Electrical engineering | |
| dc.title | Vision Based Surgical Tool Tracking with Robot Kinematics Prior | |
| dc.type | Thesis |
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