Deep learning-based detection of advanced AMD on retinal OCT from the UK Biobank dataset on behalf of the PINNACLE Consortium

被引:0
|
作者
Leingang, Oliver [1 ]
Bogunovic, Hrvoje [1 ]
Reiter, Gregor Sebastian [1 ]
Chakravarty, Arunava [1 ]
Menten, Martin Joseph [2 ]
Holland, Robert [2 ]
Fritsche, Lars G. [3 ]
Scholl, Hendrik P. [4 ]
Rueckert, Daniel [2 ]
Sivaprasad, Sobha [5 ]
Lotery, Andrew J. [6 ]
Schmidt-Erfurth, Ursula [1 ]
机构
[1] Med Univ Wien, Dept Ophthalmol, Vienna, Austria
[2] Tech Univ Munich, Inst AI & Informat Med, Munich, Germany
[3] Univ Michigan, Ann Arbor, MI USA
[4] Inst Mol & Clin Ophthalmol Basel, Basel, Switzerland
[5] Moorfields Eye Hosp NHS Fdn Trust, London, England
[6] Univ Southampton, Southampton, Hants, England
基金
英国惠康基金;
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
引用
收藏
页数:3
相关论文
共 50 条
  • [21] Deep Learning-Based Automatic Detection of Ellipsoid Zone Loss in Spectral-Domain OCT for Hydroxychloroquine Retinal Toxicity Screening
    De Silva, Tharindu
    Jayakar, Gopal
    Grisso, Peyton
    Hotaling, Nathan
    Chew, Emily Y.
    Cukras, Catherine A.
    OPHTHALMOLOGY SCIENCE, 2021, 1 (04):
  • [22] Automated arteriole and venule classification using deep learning for retinal images from the UK Biobank cohort
    Welikala, R. A.
    Foster, P. J.
    Whincup, P. H.
    Rudnicka, A. R.
    Owen, C. G.
    Strachan, D. P.
    Barman, S. A.
    COMPUTERS IN BIOLOGY AND MEDICINE, 2017, 90 : 23 - 32
  • [23] Deep Learning-Based Intrusion Detection System for Advanced Metering Infrastructure
    El Mrabet, Zakaria
    Ezzari, Mehdi
    Elghazi, Hassan
    Abou El Majd, Badr
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON NETWORKING, INFORMATION SYSTEMS & SECURITY (NISS19), 2019,
  • [24] A column-based deep learning method for the detection and quantification of atrophy associated with AMD in OCT scans
    Szeskin, Adi
    Yehuda, Roei
    Shmueli, Or
    Levy, Jaime
    Joskowicz, Leo
    MEDICAL IMAGE ANALYSIS, 2021, 72
  • [25] VHRShips: An Extensive Benchmark Dataset for Scalable Deep Learning-Based Ship Detection Applications
    Kizilkaya, Serdar
    Alganci, Ugur
    Sertel, Elif
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2022, 11 (08)
  • [26] A cross-dataset deep learning-based classifier for people fall detection and identification
    Delgado-Escano, Ruben
    Castro, Francisco M.
    Cozar, Julian R.
    Marin-Jimenez, Manuel J.
    Guil, Nicolas
    Casilari, Eduardo
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2020, 184
  • [27] Deep Learning-Based Automated Detection of Retinal Breaks and Detachments on Fundus Photography
    Christ, Merlin
    Habra, Oussama
    Monnin, Killian
    Vallotton, Kevin
    Sznitman, Raphael
    Wolf, Sebastian
    Zinkernagel, Martin
    Neila, Pablo Marquez
    TRANSLATIONAL VISION SCIENCE & TECHNOLOGY, 2024, 13 (04):
  • [28] Advancing deep learning-based detection of floating litter using a novel open dataset
    Jia, Tianlong
    Vallendar, Andre Jehan
    de Vries, Rinze
    Kapelan, Zoran
    Taormina, Riccardo
    FRONTIERS IN WATER, 2023, 5
  • [29] Deep learning-based automated fluid quantification in clinical routine OCT images in neovascular AMD over 5 years
    Gerendas, Bianca
    Sadeghipour, Amir
    Michl, Martin
    Goldbach, Felix
    Mylonas, Georgios
    Alten, Thomas
    Leingang, Oliver
    Sacu, Stefan
    Bogunovic, Hrvoje
    Schmidt-Erfurth, Ursula
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2021, 62 (08)
  • [30] Deep Learning-Based Clustering of OCT Images for Biomarker Discovery in Age-Related Macular Degeneration (PINNACLE Study Report 4)
    Holland, Robbie
    Kaye, Rebecca
    Hagag, Ahmed M.
    Leingang, Oliver
    Taylor, Thomas R. P.
    Bogunovic, Hrvoje
    Schmidt-Erfurth, Ursula
    Scholl, Hendrik P. N.
    Rueckert, Daniel
    Lotery, Andrew J.
    Sivaprasad, Sobha
    Menten, Martin J.
    OPHTHALMOLOGY SCIENCE, 2024, 4 (06):