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http://hdl.handle.net/11375/26062
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DC Field | Value | Language |
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dc.contributor.advisor | Wohl, Gregory | - |
dc.contributor.author | Wang, Yueru | - |
dc.date.accessioned | 2020-12-01T20:21:23Z | - |
dc.date.available | 2020-12-01T20:21:23Z | - |
dc.date.issued | 2020 | - |
dc.identifier.uri | http://hdl.handle.net/11375/26062 | - |
dc.description.abstract | The minimally invasive surgical procedure is more technically demanding than normal open-joint surgeries because of the limited vision. Thus, preoperative training for surgeons is essential. Current training for arthroscopy uses a fluoroscopy system, but that is costly, and the trainees will be at high risk under X-ray radiation exposure. The purpose of the overall project is to design an affordable arthroscopic surgical training station and no special safety procedures for trainees. Our system combines a virtual imaging system (to replace fluoroscopy) with a physical synthetic model of a hip joint. The purpose of the current project is to develop a 3D visual tracking system using low-cost Raspberry Pi cameras and to test the resolution and accuracy. Two Pi cameras were used to track markers on a surgical tool. The tracked data are intended to be used with a synthetic hip and superimposed on a CT dataset of the hip that can mimic surgery with real-time fluoroscopy. The reconstructed surgical tool can be overlaid on the virtual fluoroscopy to mimic the display in the real arthroscopic surgery. Pi cameras tracked passive coloured markers on a tool from different angles. The markers were tracked independently by colour segmentation, and positions were sent to a central computer simultaneously for 3D reconstruction. The optical tracking system supports 25fps, 1080p live video streaming. The largest errors in the X, Y and Z-axis are 12.46±0.14, 8.55±0.3, 10.09±0.42 mm respectively while the repeatability is in a range from 0.61 to 5.17 mm. These results demonstrate the possibility of using Raspberry Pi camera modules in a low-cost optical tracking system for surgical training purposes. Currently, the frame rate is low (25fps) and the error is still too large (up to 12.46mm) for use in surgical tracking. The resolution of the camera could improve when a better camera module is available. | en_US |
dc.language.iso | en | en_US |
dc.title | A Low-cost Optical Tracking System for Arthroscopic Surgical Training | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Mechanical Engineering | en_US |
dc.description.degreetype | Thesis | en_US |
dc.description.degree | Master of Applied Science (MASc) | en_US |
dc.description.layabstract | Arthroscopy is an orthopedic minimally invasive surgical procedure on the joint. Surgeons observe the interior of the joint through a miniature camera attached to the arthroscope, and a live X-ray image called fluoroscopy assists surgeons’ manipulations simultaneously. However, arthroscopy is technically demanding and requires intensive practice, and fluoroscopy exposes surgeons to X-ray radiation. Therefore, the objective of the overall project is to develop a cost-effective surgical training station with no special safety procedures required for trainees. The present work is to build a virtual fluoroscopy system without X-rays and track the surgical tool in realtime. Some passive markers attached to the surgical tool are tracked by Raspberry Pi cameras, then the tool is superimposed on the virtual fluoroscopic images reconstructed by a set of CT images of an artificial hip joint. The results demonstrate the possibility of using Raspberry Pi cameras in a low-cost optical tracking system for surgical training purposes. | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Wang_Yueru_finalsubmission2020Oct_M.A.Sc..pdf | 2.75 MB | Adobe PDF | View/Open |
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