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Real-Time Knee Alignment Check: Visual Recognition Innovation for Surgical Precision

This senior design project aims to demonstrate the application of visual recognition technology in verifying knee alignment during surgical procedures. By enhancing limb alignment methods with real-time visual recognition software, the project seeks to streamline surgical processes, making them more efficient and cost-effective for hospitals. The current method, which relies on surgeon setup and calibration, is both time-consuming and expensive. Through step-by-step development and testing of a visual recognition system, the project aims to create a more accurate and precise knee alignment verification process. By utilizing computer vision systems like OpenCV, the team plans to enhance the program's capabilities for detecting markers on a knee replacement tibial head, with a future goal of incorporating depth perception for alignment calculations.

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Real-Time Knee Alignment Check: Visual Recognition Innovation for Surgical Precision

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  1. Senior Design Project Megan Luh (BME) Hao Luo (EE) November 12, 2009 Knee Alignment Verification System Utilizing Visual Recognition Technology and Imaging

  2. Purpose • 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.

  3. Background and importance Current method is costly and time consuming Dependent on surgeon setup and calibration for accuracy

  4. Methods • Observe the actual surgical process of knee alignment • Develop a step-by-step method and apply it to a visual recognition system • Test and modify the program • Continue development to add additional features such as auto alignment

  5. Status • Currently waiting to be scheduled to observe the knee alignment surgery • Doing research on different software and computer vision systems

  6. Choosing a Computer Vision System Choices: • Matlab • LabVIEW • Java • C++ using OpenCV Criteria: • Complexity • Cost • Expandability • Efficiency • Well-Documented

  7. Result OpenCV • Useful functions concerning vision system • Highly Versatile library • Expandable using C++ • Free

  8. Future Work • Hope to move into programming stage after this week • Working at the very first step: recognition of different shapes • Measure of success: Identifying objects with the camera

  9. 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 real-time surgical procedure. • We plan to accomplish this by using software and cameras to detect markers on a knee replacement tibial head. • we hope to continue expanding the program to incorporate depth perception and to calculate alignment.

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