PhacoTrainer: Deep Learning for Cataract Surgical Videos to Track Surgical Tools.

ABSTRACT:

Purpose

The purpose of this study was to build a deep-learning model that automatically analyzes cataract surgical videos for the locations of surgical landmarks, and to derive skill-related motion metrics.

Methods

The locations of the pupil, limbus, and 8 classes of surgical instruments were identified by a 2-step algorithm: (1) mask segmentation and (2) landmark identification from the masks. To perform mask segmentation, we trained the YOLACT model on 1156 frames sampled from 268 videos and the public Cataract Dataset for Image Segmentation (CaDIS) dataset. Landmark identification was performed by fitting ellipses or lines to the contours of the masks and deriving locations of interest, including surgical tooltips and the pupil center. Landmark identification was evaluate

SUBMITTER: Yeh HH 

PROVIDER: S-EPMC10050900 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature