Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.547388
Title: X-ray based machine vision system for distal locking of intramedullary nails
Author: Junejo, Faraz
ISNI:       0000 0004 2715 8959
Awarding Body: Loughborough University
Current Institution: Loughborough University
Date of Award: 2009
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Abstract:
In surgical procedures for femoral shaft fracture treatment, current techniques for locking the distal end of intramedullary nails, using two screws, rely heavily on the use of two-dimensional X-ray images to guide three-dimensional bone drilling processes. Therefore, a large number of X-ray images are required, as the surgeon uses his/her skills and experience to locate the distal hole axes on the intramedullary nail. The long-term effects of X-ray radiation and their relation to different types of cancer still remain uncertain. Therefore, there is a need to develop a surgical technique that can limit the use of X-rays during the distal locking procedure. A Robotic-Assisted Orthopaedic Surgery System has been developed at Loughborough University named Loughborough Orthopaedic Assistant System (LOAS) to assist orthopaedic surgeons during distal-locking of intramedullary nails. It uses a calibration frame and a C-arm X-ray unit. The system simplifies the current approach as it uses only two near-orthogonal X-ray images to determine the drilling trajectory of the distal-locking holes, thereby considerably reducing irradiation to both the surgeon and patient. The LOAS differs from existing computer-assisted orthopaedic surgery systems, as it eliminates the need for optical tracking equipment which tends to clutter the operating theatre environment and requires care in maintaining the line of sight. Additionally use of optical tracking equipment makes such systems an expensive method for surgical guidance in distal-locking of intramedullary nails. This study is specifically concerned with the improvements of the existing system.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.547388  DOI: Not available
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