Stereoscopic Depth Imaging for Improved Point Cloud Generation of Skeletal Surfaces in IR-guided Orthopaedic Surgery
| dc.contributor.author | Cedervall, Mats | |
| dc.contributor.author | Dahlqvist, Oscar | |
| dc.contributor.department | Chalmers tekniska högskola / Institutionen för data och informationsteknik | sv |
| dc.contributor.department | Chalmers University of Technology / Department of Computer Science and Engineering | en |
| dc.contributor.examiner | Sintorn, Erik | |
| dc.contributor.supervisor | Assarsson, Ulf | |
| dc.date.accessioned | 2024-09-24T05:29:58Z | |
| dc.date.available | 2024-09-24T05:29:58Z | |
| dc.date.issued | 2024 | |
| dc.date.submitted | ||
| dc.description.abstract | This thesis proposes a flexible approach of combining traditional optical navigation systems with a visible light-based depth camera for aligning preoperative CT models with the corresponding bone exposed during active surgery, providing real-time feedback of implant positioning to the surgeon based on a preoperative plan. By leveraging the Intel® RealSenseTM D405 depth camera, the study investigates the benefits and challenges of using stereoscopic depth imaging for 3D reconstruction of musculoskeletal surfaces. The primary goal being to evaluate how this technology can be used to reduce surgery duration in orthopaedic total knee arthroplasty (TKA) surgery. The proposed method transforms the depth images captured using the depth camera into a navigation system’s frame of reference, accomplished through a series of preoperative calibration steps. The reconstructed intraoperative 3D model is then aligned with the CT model using iterative closest point (ICP) algorithms. This thesis also includes an investigation into using light polarisation filters, analysis of hyperparameter tuning, and accuracy evaluation of the Intel® RealSenseTM D405 camera’s depth estimation capabilities. Experimental validation includes a mock surgery on pig cadaver parts to simulate intraoperative conditions. Results demonstrate that the proposed approach achieves good alignment accuracy at around 0.5 mm, though it exhibits higher variability compared to competing methods. In conclusion, the integration of this class of depth cameras with optical navigation systems is a viable solution for improving the speed of knee registration in orthopaedic surgery, but future work is encouraged to address depth estimation inaccuracies. | |
| dc.identifier.coursecode | DATX05 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.12380/308791 | |
| dc.language.iso | eng | |
| dc.setspec.uppsok | Technology | |
| dc.subject | surgical navigation tools | |
| dc.subject | image-guided orthopaedic surgery | |
| dc.subject | total knee arthroplasty | |
| dc.subject | stereoscopic RGBD camera | |
| dc.subject | Intel® RealSenseTM D405 | |
| dc.title | Stereoscopic Depth Imaging for Improved Point Cloud Generation of Skeletal Surfaces in IR-guided Orthopaedic Surgery | |
| dc.type.degree | Examensarbete för masterexamen | sv |
| dc.type.degree | Master's Thesis | en |
| dc.type.uppsok | H | |
| local.programme | Computer systems and networks (MPCSN), MSc |