Knee Alignment Verification System Utilizing Visual Recognition Technology and Imaging

1. Knee Alignment Verification System Utilizing Visual Recognition Technology and Imaging Senior Design Project Megan Luh HaoLuo March 23 2010

2. 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

3. 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

4. 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

5. 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.

6. 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 

7. 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

8. Reason for the design • Pair of spheres • detection • Cross configuration • Perspective • Different length

9. Work completed • Marker detection • Marker tracking • Length detection

10. Work to be done • Angle calculation • 3D Marker fabrication • Export data

11. 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.

12. 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).