602 related articles for article (PubMed ID: 37876506)
1. Advancing glaucoma detection with convolutional neural networks: a paradigm shift in ophthalmology.
Haja SA; Mahadevappa V
Rom J Ophthalmol; 2023; 67(3):222-237. PubMed ID: 37876506
[TBL] [Abstract][Full Text] [Related]
2. Assessing the efficacy of 2D and 3D CNN algorithms in OCT-based glaucoma detection.
Rasel RK; Wu F; Chiariglione M; Choi SS; Doble N; Gao XR
Sci Rep; 2024 May; 14(1):11758. PubMed ID: 38783015
[TBL] [Abstract][Full Text] [Related]
3. Advancing Diabetic Retinopathy Diagnosis: Leveraging Optical Coherence Tomography Imaging with Convolutional Neural Networks.
Ahmed HS; Thrishulamurthy CJ
Rom J Ophthalmol; 2023; 67(4):398-402. PubMed ID: 38239418
[TBL] [Abstract][Full Text] [Related]
4. Retinal nerve fiber layer imaging with spectral-domain optical coherence tomography a study on diagnostic agreement with Heidelberg Retinal Tomograph.
Leung CK; Ye C; Weinreb RN; Cheung CY; Qiu Q; Liu S; Xu G; Lam DS
Ophthalmology; 2010 Feb; 117(2):267-74. PubMed ID: 19969364
[TBL] [Abstract][Full Text] [Related]
5. Deep Learning Estimation of 10-2 Visual Field Map Based on Circumpapillary Retinal Nerve Fiber Layer Thickness Measurements.
Kamalipour A; Moghimi S; Khosravi P; Jazayeri MS; Nishida T; Mahmoudinezhad G; Li EH; Christopher M; Liebmann JM; Fazio MA; Girkin CA; Zangwill L; Weinreb RN
Am J Ophthalmol; 2023 Feb; 246():163-173. PubMed ID: 36328198
[TBL] [Abstract][Full Text] [Related]
6. Evaluation of optical coherence tomography and heidelberg retinal tomography parameters in detecting early and moderate glaucoma.
Naithani P; Sihota R; Sony P; Dada T; Gupta V; Kondal D; Pandey RM
Invest Ophthalmol Vis Sci; 2007 Jul; 48(7):3138-45. PubMed ID: 17591883
[TBL] [Abstract][Full Text] [Related]
7. Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps.
Christopher M; Bowd C; Belghith A; Goldbaum MH; Weinreb RN; Fazio MA; Girkin CA; Liebmann JM; Zangwill LM
Ophthalmology; 2020 Mar; 127(3):346-356. PubMed ID: 31718841
[TBL] [Abstract][Full Text] [Related]
8. Variations in optic nerve head morphology by intraocular pressure in open-angle glaucoma.
Wong A; Matheos K; Prime Z; Danesh-Meyer HV
Graefes Arch Clin Exp Ophthalmol; 2017 Nov; 255(11):2219-2226. PubMed ID: 28875349
[TBL] [Abstract][Full Text] [Related]
9. Artificial intelligence in ophthalmology.
Popescu Patoni SI; Muşat AAM; Patoni C; Popescu MN; Munteanu M; Costache IB; Pîrvulescu RA; Mușat O
Rom J Ophthalmol; 2023; 67(3):207-213. PubMed ID: 37876505
[TBL] [Abstract][Full Text] [Related]
10. From Machine to Machine: An OCT-Trained Deep Learning Algorithm for Objective Quantification of Glaucomatous Damage in Fundus Photographs.
Medeiros FA; Jammal AA; Thompson AC
Ophthalmology; 2019 Apr; 126(4):513-521. PubMed ID: 30578810
[TBL] [Abstract][Full Text] [Related]
11. [Aiming for zero blindness].
Nakazawa T
Nippon Ganka Gakkai Zasshi; 2015 Mar; 119(3):168-93; discussion 194. PubMed ID: 25854109
[TBL] [Abstract][Full Text] [Related]
12. Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks.
Thakoor KA; Li X; Tsamis E; Sajda P; Hood DC
Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():2036-2040. PubMed ID: 31946301
[TBL] [Abstract][Full Text] [Related]
13. Glaucoma Diagnosis with Machine Learning Based on Optical Coherence Tomography and Color Fundus Images.
An G; Omodaka K; Hashimoto K; Tsuda S; Shiga Y; Takada N; Kikawa T; Yokota H; Akiba M; Nakazawa T
J Healthc Eng; 2019; 2019():4061313. PubMed ID: 30911364
[TBL] [Abstract][Full Text] [Related]
14. Detection of Progressive Glaucomatous Optic Nerve Damage on Fundus Photographs with Deep Learning.
Medeiros FA; Jammal AA; Mariottoni EB
Ophthalmology; 2021 Mar; 128(3):383-392. PubMed ID: 32735906
[TBL] [Abstract][Full Text] [Related]
15. Multimodal Machine Learning Using Visual Fields and Peripapillary Circular OCT Scans in Detection of Glaucomatous Optic Neuropathy.
Xiong J; Li F; Song D; Tang G; He J; Gao K; Zhang H; Cheng W; Song Y; Lin F; Hu K; Wang P; Olivia Li JP; Aung T; Qiao Y; Zhang X; Ting D
Ophthalmology; 2022 Feb; 129(2):171-180. PubMed ID: 34339778
[TBL] [Abstract][Full Text] [Related]
16. Early Detection of Optic Nerve Changes on Optical Coherence Tomography Using Deep Learning for Risk-Stratification of Papilledema and Glaucoma.
Li A; Tandon AK; Sun G; Dinkin MJ; Oliveira C
J Neuroophthalmol; 2024 Mar; 44(1):47-52. PubMed ID: 37494177
[TBL] [Abstract][Full Text] [Related]
17. Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression.
Christopher M; Belghith A; Weinreb RN; Bowd C; Goldbaum MH; Saunders LJ; Medeiros FA; Zangwill LM
Invest Ophthalmol Vis Sci; 2018 Jun; 59(7):2748-2756. PubMed ID: 29860461
[TBL] [Abstract][Full Text] [Related]
18. Detecting glaucoma based on spectral domain optical coherence tomography imaging of peripapillary retinal nerve fiber layer: a comparison study between hand-crafted features and deep learning model.
Zheng C; Xie X; Huang L; Chen B; Yang J; Lu J; Qiao T; Fan Z; Zhang M
Graefes Arch Clin Exp Ophthalmol; 2020 Mar; 258(3):577-585. PubMed ID: 31811363
[TBL] [Abstract][Full Text] [Related]
19. Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs.
Li F; Yan L; Wang Y; Shi J; Chen H; Zhang X; Jiang M; Wu Z; Zhou K
Graefes Arch Clin Exp Ophthalmol; 2020 Apr; 258(4):851-867. PubMed ID: 31989285
[TBL] [Abstract][Full Text] [Related]
20. Optic nerve head and fibre layer imaging for diagnosing glaucoma.
Michelessi M; Lucenteforte E; Oddone F; Brazzelli M; Parravano M; Franchi S; Ng SM; Virgili G
Cochrane Database Syst Rev; 2015 Nov; 2015(11):CD008803. PubMed ID: 26618332
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]