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A Fully Automatic Postoperative Appearance Prediction System for Blepharoptosis Surgery with Image-based Deep

Yiming Sun1, Xingru Huang2, Qianni Zhang2

  • 1Department of Ophthalmology, The Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China.

Ophthalmology Science
|October 17, 2022
PubMed
Summary
This summary is machine-generated.

A new deep learning system accurately predicts blepharoptosis surgery outcomes, enhancing patient understanding and satisfaction. This AI tool aids in managing expectations and can guide surgeon selection and recovery.

Keywords:
BlepharoptosisDeep learningGAN, generative adversarial networkMPLD, midpupil lid distanceMRD1, marginal reflex distance-1POAP, postoperative appearance prediction systemPostoperative prediction

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Area of Science:

  • Ophthalmology
  • Artificial Intelligence
  • Medical Imaging

Background:

  • Blepharoptosis surgery aims to correct eyelid drooping.
  • Accurate prediction of postoperative appearance is crucial for patient satisfaction.
  • Current methods for predicting surgical outcomes have limitations.

Purpose of the Study:

  • To develop and evaluate a deep learning system for predicting postoperative blepharoptosis surgery appearance.
  • To assess the accuracy and patient/clinician satisfaction with AI-generated predictions.

Main Methods:

  • A deep learning system (POAP) with four modules was trained on 970 image pairs from 362 patients.
  • System performance was evaluated using overlap ratios and lid contour analysis (MPLDs).
  • Ophthalmologists and patients rated satisfaction and similarity of predicted vs. actual outcomes.

Main Results:

  • The system achieved a high overall overlap ratio (0.858 ± 0.082).
  • Predicted lid contours showed no significant difference from real postoperative results (P > 0.05).
  • High satisfaction rates were reported by experts (35.7% satisfied, 56.0% highly satisfied) and patients.

Conclusions:

  • The AI-based method accurately predicts blepharoptosis surgery results.
  • The system enhances patient understanding of expected changes, reducing anxiety.
  • This tool can assist patients in surgeon selection and recovery, and guide less experienced surgeons.