Automatic eye localization for hospitalized infants and children using convolutional neural networks.

Journal: International journal of medical informatics
Published Date:

Abstract

BACKGROUND: Reliable localization and tracking of the eye region in the pediatric hospital environment is a significant challenge for clinical decision support and patient monitoring applications. Existing work in eye localization achieves high performance on adult datasets but performs poorly in the busy pediatric hospital environment, where face appearance varies because of age, position and the presence of medical equipment.

Authors

  • Vanessa Prinsen
    École de technologie supérieure, 1100 Notre-Dame St W, Montréal, Québec H3C 1K3 Canada; CHU Sainte-Justine, 3175 Chemin de la Côte-Sainte-Catherine, Montréal, QC H3T 1C5. Electronic address: vanessa.prinsen.1@ens.etsmtl.ca.
  • Philippe Jouvet
  • Sally Al Omar
    Université de Montréal, 2900 Edouard Montpetit Blvd, Montréal, Québec H3T 1J4 Canada.
  • Gabriel Masson
    CHU Lille, Pôle Anesthésie Réanimation, Lille, France.
  • Armelle Bridier
    Université de Montréal, 2900 Edouard Montpetit Blvd, Montréal, Québec H3T 1J4 Canada.
  • Rita Noumeir
    Electrical Engineering Department, École de Technologies Supérieure, Montreal, QC H3C 1K3, Canada.