Deep Learning Identifies High-Quality Fundus Photographs and Increases Accuracy in Automated Primary Open Angle Glaucoma Detection-Reference-Cited by-同舟云学术

Deep Learning Identifies High-Quality Fundus Photographs and Increases Accuracy in Automated Primary Open Angle Glaucoma Detection

Published:2024-01-29 Issue:1 Volume:13 Page:23
ISSN:2164-2591
Container-title:Translational Vision Science & Technology
language:en
Short-container-title:Trans. Vis. Sci. Tech.

Author:

Chuter Benton¹,Huynh Justin¹,Bowd Christopher¹,Walker Evan¹,Rezapour Jasmin¹²,Brye Nicole¹,Belghith Akram¹,Fazio Massimo A.³,Girkin Christopher A.³,De Moraes Gustavo⁴,Liebmann Jeffrey M.⁴,Weinreb Robert N.¹,Zangwill Linda M.¹,Christopher Mark¹

Affiliation:

1. Hamilton Glaucoma Center, Shiley Eye Institute, Viterbi Family Department of Ophthalmology, UC San Diego, La Jolla, California, United States

2. Department of Ophthalmology, University Medical Center Mainz, Germany

3. School of Medicine, Callahan Eye Hospital, University of Alabama-Birmingham, Birmingham, Alabama, United States

4. Bernard and Shirlee Brown Glaucoma Research Laboratory, Edward S. Harkness Eye Institute, Department of Ophthalmology, Columbia University Medical Center, New York, New York, United States

Publisher

Association for Research in Vision and Ophthalmology (ARVO)

Reference34 articles.

1. Glaucoma detection based on deep convolutional neural network;Xiangyu;Annu Int Conf IEEE Eng Med Biol Soc,2015

2. Performance of deep learning architectures and transfer learning for detecting glaucomatous optic neuropathy in fundus photographs;Christopher;Sci Rep,2018

3. Effects of study population, labeling and training on glaucoma detection using deep learning algorithms;Christopher;Transl Vis Sci Technol,2020

4. Human visual system-based fundus image quality assessment of portable fundus camera photographs;Wang;IEEE Trans Med Imaging,2016

5. Quality evaluation of digital fundus images through combined measures;Veiga;J Med Imaging (Bellingham),2014

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