178 related articles for article (PubMed ID: 29564864)
1. Automatic diagnosis of abnormal macula in retinal optical coherence tomography images using wavelet-based convolutional neural network features and random forests classifier.
Rasti R; Mehridehnavi A; Rabbani H; Hajizadeh F
J Biomed Opt; 2018 Mar; 23(3):1-10. PubMed ID: 29564864
[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. 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]
4. Fully Automated Segmentation of Fluid/Cyst Regions in Optical Coherence Tomography Images With Diabetic Macular Edema Using Neutrosophic Sets and Graph Algorithms.
Rashno A; Koozekanani DD; Drayna PM; Nazari B; Sadri S; Rabbani H; Parhi KK
IEEE Trans Biomed Eng; 2018 May; 65(5):989-1001. PubMed ID: 28783619
[TBL] [Abstract][Full Text] [Related]
5. Wavelet scattering transform application in classification of retinal abnormalities using OCT images.
Baharlouei Z; Rabbani H; Plonka G
Sci Rep; 2023 Nov; 13(1):19013. PubMed ID: 37923770
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. 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]
8. Three-dimensional analysis of retinal layer texture: identification of fluid-filled regions in SD-OCT of the macula.
Quellec G; Lee K; Dolejsi M; Garvin MK; Abràmoff MD; Sonka M
IEEE Trans Med Imaging; 2010 Jun; 29(6):1321-30. PubMed ID: 20363675
[TBL] [Abstract][Full Text] [Related]
9. Intraretinal layer segmentation of macular optical coherence tomography images using optimal 3-D graph search.
Garvin MK; Abramoff MD; Kardon R; Russell SR; Wu X; Sonka M
IEEE Trans Med Imaging; 2008 Oct; 27(10):1495-505. PubMed ID: 18815101
[TBL] [Abstract][Full Text] [Related]
10. Machine learning techniques for diabetic macular edema (DME) classification on SD-OCT images.
Alsaih K; Lemaitre G; Rastgoo M; Massich J; Sidibé D; Meriaudeau F
Biomed Eng Online; 2017 Jun; 16(1):68. PubMed ID: 28592309
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Computerized macular pathology diagnosis in spectral domain optical coherence tomography scans based on multiscale texture and shape features.
Liu YY; Ishikawa H; Chen M; Wollstein G; Duker JS; Fujimoto JG; Schuman JS; Rehg JM
Invest Ophthalmol Vis Sci; 2011 Oct; 52(11):8316-22. PubMed ID: 21911579
[TBL] [Abstract][Full Text] [Related]
13. Automated macular pathology diagnosis in retinal OCT images using multi-scale spatial pyramid and local binary patterns in texture and shape encoding.
Liu YY; Chen M; Ishikawa H; Wollstein G; Schuman JS; Rehg JM
Med Image Anal; 2011 Oct; 15(5):748-59. PubMed ID: 21737338
[TBL] [Abstract][Full Text] [Related]
14. Automatic classification of retinal three-dimensional optical coherence tomography images using principal component analysis network with composite kernels.
Fang L; Wang C; Li S; Yan J; Chen X; Rabbani H
J Biomed Opt; 2017 Nov; 22(11):1-10. PubMed ID: 29188661
[TBL] [Abstract][Full Text] [Related]
15. An anomaly detection approach for the identification of DME patients using spectral domain optical coherence tomography images.
Sidibé D; Sankar S; Lemaître G; Rastgoo M; Massich J; Cheung CY; Tan GSW; Milea D; Lamoureux E; Wong TY; Mériaudeau F
Comput Methods Programs Biomed; 2017 Feb; 139():109-117. PubMed ID: 28187882
[TBL] [Abstract][Full Text] [Related]
16. Automated macular pathology diagnosis in retinal OCT images using multi-scale spatial pyramid with local binary patterns.
Liu YY; Chen M; Ishikawa H; Wollstein G; Schuman JS; Rehg JM
Med Image Comput Comput Assist Interv; 2010; 13(Pt 1):1-9. PubMed ID: 20879208
[TBL] [Abstract][Full Text] [Related]
17. [A segmentation algorithm of OCT image for macula edema].
Yang P; Peng Q; Lin W; Yang X
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2011 Oct; 28(5):1001-6. PubMed ID: 22097272
[TBL] [Abstract][Full Text] [Related]
18. High-definition and 3-dimensional imaging of macular pathologies with high-speed ultrahigh-resolution optical coherence tomography.
Srinivasan VJ; Wojtkowski M; Witkin AJ; Duker JS; Ko TH; Carvalho M; Schuman JS; Kowalczyk A; Fujimoto JG
Ophthalmology; 2006 Nov; 113(11):2054.e1-14. PubMed ID: 17074565
[TBL] [Abstract][Full Text] [Related]
19. Use of a Neural Net to Model the Impact of Optical Coherence Tomography Abnormalities on Vision in Age-related Macular Degeneration.
Aslam TM; Zaki HR; Mahmood S; Ali ZC; Ahmad NA; Thorell MR; Balaskas K
Am J Ophthalmol; 2018 Jan; 185():94-100. PubMed ID: 29101008
[TBL] [Abstract][Full Text] [Related]
20. A computer-aided diagnostic system for detecting diabetic retinopathy in optical coherence tomography images.
ElTanboly A; Ismail M; Shalaby A; Switala A; El-Baz A; Schaal S; Gimel'farb G; El-Azab M
Med Phys; 2017 Mar; 44(3):914-923. PubMed ID: 28035657
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
