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Senior Design Project Megan Luh Hao Luo March 23 2010
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Total Knee Arthroplasty (TKA) One of the most common orthopedic procedures performed Surgeon removes damaged bone surfaces using implant specific jigs Attaches implants that mimic shape of the natural knee 90% successful but 10% are misaligned Cause pain and will require another surgery
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Solutions to the alignment problem Praxim Computer guidance system Three trackers attached to infrared cameras Placed on pelvis, femur, and tibia Accuracy of system depends on surgeon placement of trackers Costly Requires set up and take down time
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Analysis Problem Statement Current methods of limb alignment are costly and time consuming Dependent on individual surgeon skill for accurate calibration Performance Criteria Constrained by surgical space, time, and resources Limited by lens quality, camera resolution and frame rate, and noise level
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Primary Objective Proof of Concept that visual recognition software can be applied to the field of limb alignment in real-time for surgical procedures Improve the method of limb alignment used during surgical procedures Create a new method that is more efficient, can be used in real-time, more economically profitable for hospitals.
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Factors Parameters Quality is determined by the speed, accuracy, and precision of the computer algorithm Overall operating costs are reduced with a faster system Patient and surgeon both benefit from a faster, more accurate system Average operating room costs = $1000.00 per min Surgical costs Doctor visits; pre surgery and exams (total 3) $512 MRI $992.00 Hospital $4,909 Anesthesia 718.20 Doctor Charge: $3591 (surgery) total amounts =10,722.20
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Marker Designing a cross shape marker with some spheres on it to mark the x-ray Use a biocompatible, disposable plastic with an x- ray contrast medium: polyethylene, polycarbonate It consists of four spheres connected in a cross configuration The two pairs of spheres vary in size and in color
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Reason for the design Pair of spheres detection Cross configuration Perspective Different length
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Work completed Marker detection Marker tracking Length detection
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Work to be done Angle calculation 3D Marker fabrication Export data
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Conclusion The goal of this project is to accomplish a proof of concept that visual recognition software can be applied to the field of orthopedic limb alignment in a real-time surgical procedure. So far, we have solidified the goal and mapped out the details of software implementation. Futures works include creating the software, troubleshooting, and testing the result.
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References Duda, R. O. and P. E. Hart, "Use of the Hough Transformation to Detect Lines and Curves in Pictures," Comm. ACM, Vol. 15, pp. 11–15 (January, 1972). Bradski, Gary, and Adrian Kaehler. "Image Transforms, Contours, Project and 3D vision." In Learning OpenCV: Computer Vision with the OpenCV Library. 1st ed. Sebastopol: O'Reilly Media, Inc., 2008. 109-141, 144-190, 222-251, 370-458. Chleborad, Aaron. "OpenCV's cvReprojectImageTo3D." Graduate Student Robotics Blog. http://people.cis.ksu.edu/~aaron123/?m=20090629 (accessed December 18, 2009).
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