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CMOS Image Sensor Design and Image Processing Algorithm Implementation for Total Hip Arthroplasty Surgery.

Syed Mudassir Hussain, Fasih Ud Din Farrukh, Shaojie Su

    IEEE Transactions on Biomedical Circuits and Systems
    |October 16, 2019
    PubMed
    Summary

    This study introduces a miniaturized CMOS image sensor and advanced pattern recognition for hip replacement surgery. The system enhances surgical accuracy and significantly reduces power consumption, improving patient outcomes.

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    Area of Science:

    • Biomedical Engineering
    • Microsystems Engineering
    • Computer Vision

    Background:

    • Hip arthroplasty is increasingly common due to an aging population.
    • Existing visual-aided systems face integration, size, and power challenges.
    • Minimizing implant size and power is crucial for patient safety and system efficacy.

    Purpose of the Study:

    • To develop a miniaturized CMOS image sensor for hip arthroplasty.
    • To create a robust pattern detection and recognition method for intraoperative use.
    • To reduce overall system power consumption for enhanced practicality.

    Main Methods:

    • Designed and simulated a 200x200 resolution CMOS image sensor (3.5mm x 3.5mm).
    • Developed a novel pattern detection algorithm for blood-covered surfaces.
    • Implemented image processing algorithms on FPGA for efficient data handling.

    Main Results:

    • Achieved a 99% pattern detection rate, outperforming the top hat algorithm by 5%.
    • Demonstrated a 70% reduction in power consumption (213 mW) compared to previous systems.
    • Validated sensor performance across a wide input current range (2 pA to 100 pA).

    Conclusions:

    • The proposed miniaturized sensor and pattern recognition system are highly effective for hip arthroplasty.
    • Significant reductions in size and power consumption were achieved.
    • The system offers improved accuracy and efficiency for surgical navigation.