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Related Experiment Video

Updated: Sep 6, 2025

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Intelligent cataract surgery supervision and evaluation via deep learning.

Ting Wang¹, Jun Xia², Ruiyang Li¹

¹State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Vision Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, Guangdong, China.

International Journal of Surgery (London, England)

|June 27, 2022

Summary

A new deep learning (DL) algorithm, DeepSurgery, accurately evaluates cataract surgery (CS) steps from videos. This AI tool can supervise procedures and improve surgical outcomes.

Keywords:

Action recognition Artificial intelligence Cataract surgery Evaluation

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Last Updated: Sep 6, 2025

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Area of Science:

Ophthalmology
Artificial Intelligence
Surgical Technology

Background:

Cataract surgery (CS) requires precise execution and objective evaluation.
Supervising and assessing surgical performance can be subjective and time-consuming.

Purpose of the Study:

To evaluate a deep learning (DL) algorithm, DeepSurgery, for real-time supervision and objective assessment of cataract extraction with intraocular lens (IOL) implantation using surgical videos.

Main Methods:

DeepSurgery was trained on 186 cataract surgery videos to recognize 12 surgical steps.
Validation involved two datasets (50 and 21 videos) and a supervision test with 50 videos.
Real-time performance was compared against expert panels and residents using 54 surgeries.

Main Results:

DeepSurgery demonstrated high accuracy in recognizing surgical steps (95.06% internal, 88.77-88.34% external validation).
The algorithm correctly identified surgical chronology and alerted to errors, achieving 90.30% accuracy in real-time tests.
DeepSurgery's performance in assessing surgical steps was comparable to expert panels (kappa 0.58-0.77).

Conclusions:

DeepSurgery offers a potential solution for real-time surgical supervision and objective evaluation in routine cataract surgery.
This AI-driven system may contribute to improving overall surgical outcomes.