2434 related articles for article (PubMed ID: 30610422)
1. Fully automated detection of retinal disorders by image-based deep learning.
Li F; Chen H; Liu Z; Zhang X; Wu Z
Graefes Arch Clin Exp Ophthalmol; 2019 Mar; 257(3):495-505. PubMed ID: 30610422
[TBL] [Abstract][Full Text] [Related]
2. OCT-based deep learning algorithm for the evaluation of treatment indication with anti-vascular endothelial growth factor medications.
Prahs P; Radeck V; Mayer C; Cvetkov Y; Cvetkova N; Helbig H; Märker D
Graefes Arch Clin Exp Ophthalmol; 2018 Jan; 256(1):91-98. PubMed ID: 29127485
[TBL] [Abstract][Full Text] [Related]
3. Fully Automated Detection and Quantification of Macular Fluid in OCT Using Deep Learning.
Schlegl T; Waldstein SM; Bogunovic H; Endstraßer F; Sadeghipour A; Philip AM; Podkowinski D; Gerendas BS; Langs G; Schmidt-Erfurth U
Ophthalmology; 2018 Apr; 125(4):549-558. PubMed ID: 29224926
[TBL] [Abstract][Full Text] [Related]
4. Deep Residual Network for Diagnosis of Retinal Diseases Using Optical Coherence Tomography Images.
Asif S; Amjad K; Qurrat-Ul-Ain
Interdiscip Sci; 2022 Dec; 14(4):906-916. PubMed ID: 35767116
[TBL] [Abstract][Full Text] [Related]
5. The possibility of the combination of OCT and fundus images for improving the diagnostic accuracy of deep learning for age-related macular degeneration: a preliminary experiment.
Yoo TK; Choi JY; Seo JG; Ramasubramanian B; Selvaperumal S; Kim DW
Med Biol Eng Comput; 2019 Mar; 57(3):677-687. PubMed ID: 30349958
[TBL] [Abstract][Full Text] [Related]
6. Classification of diabetes-related retinal diseases using a deep learning approach in optical coherence tomography.
Perdomo O; Rios H; Rodríguez FJ; Otálora S; Meriaudeau F; Müller H; González FA
Comput Methods Programs Biomed; 2019 Sep; 178():181-189. PubMed ID: 31416547
[TBL] [Abstract][Full Text] [Related]
7. Optical coherence tomography for age-related macular degeneration and diabetic macular edema: an evidence-based analysis.
Medical Advisory Secretariat
Ont Health Technol Assess Ser; 2009; 9(13):1-22. PubMed ID: 23074517
[TBL] [Abstract][Full Text] [Related]
8. A new intelligent system based deep learning to detect DME and AMD in OCT images.
Gueddena Y; Aboudi N; Zgolli H; Mabrouk S; Sidibe D; Tabia H; Khlifa N
Int Ophthalmol; 2024 Apr; 44(1):191. PubMed ID: 38653842
[TBL] [Abstract][Full Text] [Related]
9. Multi-scale convolutional neural network for automated AMD classification using retinal OCT images.
Sotoudeh-Paima S; Jodeiri A; Hajizadeh F; Soltanian-Zadeh H
Comput Biol Med; 2022 May; 144():105368. PubMed ID: 35259614
[TBL] [Abstract][Full Text] [Related]
10. Stitched vision transformer for age-related macular degeneration detection using retinal optical coherence tomography images.
Azizi MM; Abhari S; Sajedi H
PLoS One; 2024; 19(6):e0304943. PubMed ID: 38837967
[TBL] [Abstract][Full Text] [Related]
11. Classification of healthy and diseased retina using SD-OCT imaging and Random Forest algorithm.
Hussain MA; Bhuiyan A; D Luu C; Theodore Smith R; H Guymer R; Ishikawa H; S Schuman J; Ramamohanarao K
PLoS One; 2018; 13(6):e0198281. PubMed ID: 29864167
[TBL] [Abstract][Full Text] [Related]
12. AOCT-NET: a convolutional network automated classification of multiclass retinal diseases using spectral-domain optical coherence tomography images.
Alqudah AM
Med Biol Eng Comput; 2020 Jan; 58(1):41-53. PubMed ID: 31728935
[TBL] [Abstract][Full Text] [Related]
13. Development and Validation of Deep Learning Models for Screening Multiple Abnormal Findings in Retinal Fundus Images.
Son J; Shin JY; Kim HD; Jung KH; Park KH; Park SJ
Ophthalmology; 2020 Jan; 127(1):85-94. PubMed ID: 31281057
[TBL] [Abstract][Full Text] [Related]
14. Fully automated macular pathology detection in retina optical coherence tomography images using sparse coding and dictionary learning.
Sun Y; Li S; Sun Z
J Biomed Opt; 2017 Jan; 22(1):16012. PubMed ID: 28114453
[TBL] [Abstract][Full Text] [Related]
15. Automatic detection of retinal regions using fully convolutional networks for diagnosis of abnormal maculae in optical coherence tomography images.
Sun Z; Sun Y
J Biomed Opt; 2019 May; 24(5):1-9. PubMed ID: 31111697
[TBL] [Abstract][Full Text] [Related]
16. Automated detection of exudative age-related macular degeneration in spectral domain optical coherence tomography using deep learning.
Treder M; Lauermann JL; Eter N
Graefes Arch Clin Exp Ophthalmol; 2018 Feb; 256(2):259-265. PubMed ID: 29159541
[TBL] [Abstract][Full Text] [Related]
17. Development and Clinical Validation of Semi-Supervised Generative Adversarial Networks for Detection of Retinal Disorders in Optical Coherence Tomography Images Using Small Dataset.
Zheng C; Ye H; Yang J; Fei P; Qiu Y; Xie X; Wang Z; Chen J; Zhao P
Asia Pac J Ophthalmol (Phila); 2022 May; 11(3):219-226. PubMed ID: 35342179
[TBL] [Abstract][Full Text] [Related]
18. Epiretinal Membrane Detection at the Ophthalmologist Level using Deep Learning of Optical Coherence Tomography.
Lo YC; Lin KH; Bair H; Sheu WH; Chang CS; Shen YC; Hung CL
Sci Rep; 2020 May; 10(1):8424. PubMed ID: 32439844
[TBL] [Abstract][Full Text] [Related]
19. Deep Ensemble Learning Based Objective Grading of Macular Edema by Extracting Clinically Significant Findings from Fused Retinal Imaging Modalities.
Hassan B; Hassan T; Li B; Ahmed R; Hassan O
Sensors (Basel); 2019 Jul; 19(13):. PubMed ID: 31284442
[TBL] [Abstract][Full Text] [Related]
20. A supervised joint multi-layer segmentation framework for retinal optical coherence tomography images using conditional random field.
Chakravarty A; Sivaswamy J
Comput Methods Programs Biomed; 2018 Oct; 165():235-250. PubMed ID: 30337078
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
