PeriorbitAI: Artificial Intelligence Automation of Eyelid and Periorbital Measurements.

Journal: American journal of ophthalmology
Published Date: Oct 1, 2021

Abstract

PURPOSE: To develop a deep learning semantic segmentation network to automate the assessment of 8 periorbital measurements DESIGN: Development and validation of an artificial intelligence (AI) segmentation algorithm METHODS: A total of 418 photographs of periorbital areas were used to train a deep learning semantic segmentation model to segment iris, aperture, and brow areas. These data were used to develop a post-processing algorithm that measured margin reflex distance (MRD) 1 and 2, medial canthal height (MCH), lateral canthal height (LCH), medial brow height (MBH), lateral brow height (LBH), medial intercanthal distance (MID), and lateral intercanthal distance (LID). The algorithm validity was evaluated on a prospective hold-out test set against 3 graders. The main outcome measures were dice coefficient, mean absolute difference, intraclass correlation coefficient, and Bland-Altman analysis. A smartphone video was also segmented and evaluated as proof of concept.

Authors

  • Alexandra Van Brummen
    From the Department of Ophthalmology, University of Washington, Seattle, Washington.
  • Julia P Owen
    Department of Ophthalmology, University of Washington, Seattle, Washington.
  • Theodore Spaide
    Department of Ophthalmology, School of Medicine, University of Washington, Seattle, WA, USA.
  • Colin Froines
    From the Department of Ophthalmology, University of Washington, Seattle, Washington.
  • Randy Lu
    From the Department of Ophthalmology, University of Washington, Seattle, Washington.
  • Megan Lacy
    From the Department of Ophthalmology, University of Washington, Seattle, Washington.
  • Marian Blazes
    From the Department of Ophthalmology, University of Washington, Seattle, Washington.
  • Emily Li
    From the Department of Ophthalmology, University of Washington, Seattle, Washington.
  • Cecilia S Lee
    Department of Ophthalmology, University of Washington, Seattle, Washington, USA.
  • Aaron Y Lee
    Department of Ophthalmology, University of Washington, Seattle, Washington.
  • Matthew Zhang
    From the Department of Ophthalmology, University of Washington, Seattle, Washington. Electronic address: venwu@uw.edu.

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