Multimodal, multitask, multiattention (M3) deep learning detection of reticular pseudodrusen: Toward automated and accessible classification of age-related macular degeneration.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date:

Abstract

OBJECTIVE: Reticular pseudodrusen (RPD), a key feature of age-related macular degeneration (AMD), are poorly detected by human experts on standard color fundus photography (CFP) and typically require advanced imaging modalities such as fundus autofluorescence (FAF). The objective was to develop and evaluate the performance of a novel multimodal, multitask, multiattention (M3) deep learning framework on RPD detection.

Authors

  • Qingyu Chen
    Department of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA.
  • Tiarnan D L Keenan
    Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, Maryland.
  • Alexis Allot
    National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA; email: zhiyong.lu@nih.gov.
  • Yifan Peng
    Department of Population Health Sciences, Weill Cornell Medicine, New York, USA.
  • Elvira Agrón
    National Eye Institute, National Institutes of Health, Bethesda, Maryland.
  • Amitha Domalpally
    Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America.
  • Caroline C W Klaver
    Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands; Department of Ophthalmology, Erasmus University Medical Center, Rotterdam, The Netherlands; Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands; Department of Ophthalmology, Radboud University Medical Center, Nijmegen, The Netherlands; Institute for Molecular and Clinical Ophthalmology, Basel, Switzerland.
  • Daniël T Luttikhuizen
    Erasmus MC, afd. Oogheelkunde en afd. Epidemiologie, Rotterdam.
  • Marcus H Colyer
    Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA.
  • Catherine A Cukras
    Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, Maryland, USA.
  • Henry E Wiley
    Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, Maryland, USA.
  • M Teresa Magone
    Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, Maryland, USA.
  • Chantal Cousineau-Krieger
    Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, Maryland, USA.
  • Wai T Wong
    National Eye Institute, National Institutes of Health, Bethesda, Maryland.
  • Yingying Zhu
    Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, USA.
  • Emily Y Chew
    National Eye Institute, National Institutes of Health, Bethesda, Maryland. Electronic address: echew@nei.nih.gov.
  • Zhiyong Lu
    National Center for Biotechnology Information, Bethesda, MD 20894 USA.