Convolutional Neural Network Using RNFL Thickness Maps for Diagnosis of Glaucoma

被引:0
|
作者
Wang, Peiyu [1 ]
Moloney, Maemae [2 ]
Torres, Mina [3 ]
Jiang, Xuejuan [3 ]
Rodger, Damien C. [1 ,3 ]
Varma, Rohit [3 ]
Richter, Grace [3 ]
机构
[1] Univ Southern Calif, Biomed Engn, Los Angeles, CA USA
[2] Univ Southern Calif, Dept Neurosci, Los Angeles, CA USA
[3] Univ Southern Calif, Roski Eye Inst, Los Angeles, CA USA
关键词
D O I
暂无
中图分类号
R77 [眼科学];
学科分类号
100212 ;
摘要
4075
引用
收藏
页数:7
相关论文
共 50 条
  • [1] Deep neural network based glaucoma detection using RNFL thickness map
    Patel, Krunalkumar Ramanbhai
    Lee, Gary C.
    Durbin, Mary K.
    Wall, Michael
    Artes, Paul H.
    Flanagan, John G.
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2019, 60 (09)
  • [2] Comparison of RNFL thickness and RPE-normalized RNFL attenuation coefficient for glaucoma diagnosis
    Vermeer, K. A.
    van der Schoot, J.
    Lemij, H. G.
    de Boer, J. F.
    OPHTHALMIC TECHNOLOGIES XXIII, 2013, 8567
  • [3] Automatic Glaucoma Diagnosis in Digital Fundus images using Convolutional Neural Network
    Sharma, Ambika
    Aggarwal, Monika
    Roy, Sumantra Dutta
    Gupta, Vivek
    PROCEEDINGS OF 2019 5TH IEEE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, COMPUTING AND CONTROL (ISPCC 2K19), 2019, : 160 - 165
  • [4] Visual Field Based Automatic Diagnosis of Glaucoma Using Deep Convolutional Neural Network
    Li, Fei
    Wang, Zhe
    Qu, Guoxiang
    Qiao, Yu
    Zhang, Xiulan
    COMPUTATIONAL PATHOLOGY AND OPHTHALMIC MEDICAL IMAGE ANALYSIS, 2018, 11039 : 285 - 293
  • [5] Combining OCT Corneal Topography and Thickness Maps to Diagnose Keratoconus Using a Convolutional Neural Network
    Pavlatos, Elias
    Huang, David
    Li, Yan
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2022, 63 (07)
  • [6] Investigation of the Role of Convolutional Neural Network Architectures in the Diagnosis of Glaucoma using Color Fundus Photography
    Atalay, Eray
    Ozalp, Onur
    Devecioglu, Ozer Can
    Erdogan, Hakika
    Ince, Turker
    Yildirim, Nilgun
    TURK OFTALMOLOJI DERGISI-TURKISH JOURNAL OF OPHTHALMOLOGY, 2022, 52 (03): : 193 - 200
  • [7] Visual Field-based Automatic Diagnosis of Glaucoma Using Deep Convolutional Neural Network
    Li, Fei
    Gao, Kai
    Wang, Zhe
    Qu, Guoxiang
    Zhong, Hua
    Qiao, Yu
    Zhang, Xiulan
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2018, 59 (09)
  • [8] In-Depth Evaluation of Saliency Maps for Interpreting Convolutional Neural Network Decisions in the Diagnosis of Glaucoma Based on Fundus Imaging
    Sigut, Jose
    Fumero, Francisco
    Estevez, Jose
    Alayon, Silvia
    Diaz-Aleman, Tinguaro
    SENSORS, 2024, 24 (01)
  • [9] Electrophysiologic Correlates of RNFL Thickness in Experimental Glaucoma
    Hoeve, James Ver
    Kim, Charlene
    Rasmussen, Carol
    Murphy, Christopher
    Christian, Brian
    Nork, T. Michael
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2013, 54 (15)
  • [10] A Comparative Study of Convolutional Neural Network and Twin SVM for Automatic Glaucoma Diagnosis
    Touahri, Radia
    Azizi, Nabiha
    Benzebouchi, Nacer Eddine
    Hammami, Nacer Eddine
    Moumene, Ouided
    2018 INTERNATIONAL CONFERENCE ON SIGNAL, IMAGE, VISION AND THEIR APPLICATIONS (SIVA), 2018,