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A computer vision-based approach to grade simulated cataract surgeries

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Abstract

To increase the timeliness, objectivity, and efficiency in evaluating ophthalmology residents’ learning of cataract surgery, an automatic analysis system for cataract surgery videos is developed to assess performance, particularly in the capsulorhexis step on the Kitaro simulator. We utilize computer vision technologies to measure performance of this critical step including duration, size, centrality, circularity, as well as motion stability during the capsulorhexis procedure. Consequently, a grading mechanism is established based on either linear regression or non-linear classification via Support Vector Machine of those computed measures. Comparisons of expert graders to the computer vision-based approach have demonstrated the accuracy and consistency of the computerized technique.

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Acknowledgments

This work is supported by the Flaum Eye Institute, University of Rochester Medical Center. I would like to thank Dr. William Gensheimer for the expert’s grading and fruitful discussions.

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Authors and Affiliations

  1. Department of Computer Science, University of Rochester, Rochester, USA

    Junhuan Zhu & Jiebo Luo

  2. Flaum Eye Institute, University of Rochester Medical Center, Rochester, USA

    Jonathan M. Soh

  3. Emory Eye Center, Emory University, Atlanta, USA

    Yousuf M. Khalifa

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  1. Junhuan Zhu
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  2. Jiebo Luo
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  3. Jonathan M. Soh
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  4. Yousuf M. Khalifa
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Correspondence to Junhuan Zhu.

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Zhu, J., Luo, J., Soh, J.M. et al. A computer vision-based approach to grade simulated cataract surgeries. Machine Vision and Applications 26, 115–125 (2015). https://doi.org/10.1007/s00138-014-0646-x

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