Construction of Quantitative Indexes for Cataract Surgery Evaluation Based on Deep Learning

Yuanyuan Gu, Yan Hu, Lei Mou, Hua Ying Hao, Yitian Zhao, Ce Zheng, Jiang Liu

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Objective and accurate evaluation of cataract surgery is a necessary way to improve the operative level of resident and shorten the learning curve. Our objective in this study is to construct quantifiable evaluation indicators through deep learning techniques to assist experts in the implementation of evaluation and verify the reliability of the evaluation indicators. We use a data set of 98 videos of incision, which is a critical step in cataract surgery. According to the visual characteristics of incision evaluation indicators specified in the International Council of Ophthalmology’s Ophthalmology Surgical Competency Assessment Rubric: phacoemulsification (ICO-OSCAR: phaco), we propose using the ResNet and ResUnet to obtain the keratome tip position and the pupil shape to construct the quantifiable evaluation indexes, such as the tool trajectory, the size and shape of incision, and the scaling of a pupil. Referring to the motion of microscope and eye movement caused by keratome pushing during the video recording, we use the center of the pupil as a reference point to calculate the exact relative motion trajectory of the surgical instrument and the incision size, which can be used to directly evaluate surgical skill. The experiment shows that the evaluation indexes we constructed have high accuracy, which is highly consistent with the evaluation of the expert surgeons group.

Original languageEnglish
Title of host publicationOphthalmic Medical Image Analysis - 7th International Workshop, OMIA 2020, Held in Conjunction with MICCAI 2020, Proceedings
EditorsHuazhu Fu, Mona K. Garvin, Tom MacGillivray, Yanwu Xu, Yalin Zheng
PublisherSpringer Science and Business Media Deutschland GmbH
Pages195-205
Number of pages11
ISBN (Print)9783030634186
DOIs
Publication statusPublished - 2020
Externally publishedYes
Event6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2020, held in conjunction with 23rd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2020 - Lima, Peru
Duration: 8 Oct 20208 Oct 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12069 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2020, held in conjunction with 23rd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2020
Country/TerritoryPeru
CityLima
Period8/10/208/10/20

Keywords

  • Cataract surgery assessment
  • Deep learning

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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