Literature DB >> 32053135

Data-Driven, Feature-Agnostic Deep Learning vs Retinal Nerve Fiber Layer Thickness for the Diagnosis of Glaucoma.

Christine A Petersen1, Parmita Mehta2,3, Aaron Y Lee1,3.   

Abstract

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Mesh：

Year:  2020        PMID： 32053135      PMCID： PMC8168282          DOI： 10.1001/jamaophthalmol.2019.6143

Source DB:  PubMed          Journal:  JAMA Ophthalmol        ISSN： 2168-6165            Impact factor:   7.389


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  5 in total

1.  Assessment of a Segmentation-Free Deep Learning Algorithm for Diagnosing Glaucoma From Optical Coherence Tomography Scans.

Authors:  Atalie C Thompson; Alessandro A Jammal; Samuel I Berchuck; Eduardo B Mariottoni; Felipe A Medeiros
Journal:  JAMA Ophthalmol       Date:  2020-04-01       Impact factor: 7.389

2.  Prevalence and Associated Factors of Segmentation Errors in the Peripapillary Retinal Nerve Fiber Layer and Macular Ganglion Cell Complex in Spectral-domain Optical Coherence Tomography Images.

Authors:  Atsuya Miki; Miho Kumoi; Shinichi Usui; Takao Endo; Rumi Kawashima; Takeshi Morimoto; Kenji Matsushita; Takashi Fujikado; Kohji Nishida
Journal:  J Glaucoma       Date:  2017-11       Impact factor: 2.503

3.  Estimating Retinal Sensitivity Using Optical Coherence Tomography With Deep-Learning Algorithms in Macular Telangiectasia Type 2.

Authors:  Yuka Kihara; Tjebo F C Heeren; Cecilia S Lee; Yue Wu; Sa Xiao; Simone Tzaridis; Frank G Holz; Peter Charbel Issa; Catherine A Egan; Aaron Y Lee
Journal:  JAMA Netw Open       Date:  2019-02-01

4.  A feature agnostic approach for glaucoma detection in OCT volumes.

Authors:  Stefan Maetschke; Bhavna Antony; Hiroshi Ishikawa; Gadi Wollstein; Joel Schuman; Rahil Garnavi
Journal:  PLoS One       Date:  2019-07-01       Impact factor: 3.240

5.  Diagnostic criteria for detection of retinal nerve fibre layer thickness and neuroretinal rim width abnormalities in glaucoma.

Authors:  Feihui Zheng; Marco Yu; Christopher Kai-Shun Leung
Journal:  Br J Ophthalmol       Date:  2019-05-30       Impact factor: 4.638
  5 in total
  1 in total

Review 1.  The use of deep learning technology for the detection of optic neuropathy.

Authors:  Mei Li; Chao Wan
Journal:  Quant Imaging Med Surg       Date:  2022-03
  1 in total

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