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    Automated Assessment of Surgical Skills Using Frequency Analysis

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    2015-Zia-AASSUFA.pdf (2.900Mb)
    Date
    2015
    Author
    Zia, Aneeq
    Sharma, Yachna
    Bettadapura, Vinay
    Sarin, Eric L.
    Clements, Mark A.
    Essa, Irfan
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    Abstract
    We present an automated framework for visual assessment of the expertise level of surgeons using the OSATS (Objective Structured Assessment of Technical Skills) criteria. Video analysis techniques for extracting motion quality via frequency coefficients are introduced. The framework is tested on videos of medical students with different expertise levels performing basic surgical tasks in a surgical training lab setting. We demonstrate that transforming the sequential time data into frequency components effectively extracts the useful information differentiating between different skill levels of the surgeons. The results show significant performance improvements using DFT and DCT coefficients over known state-of-the-art techniques.
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    http://hdl.handle.net/1853/54744
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    • Computational Perception & Robotics [213]
    • Computational Perception & Robotics Publications [213]

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