192 related articles for article (PubMed ID: 38032915)
1. CLAHE-CapsNet: Efficient retina optical coherence tomography classification using capsule networks with contrast limited adaptive histogram equalization.
Opoku M; Weyori BA; Adekoya AF; Adu K
PLoS One; 2023; 18(11):e0288663. PubMed ID: 38032915
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. 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]
4. An enhanced OCT image captioning system to assist ophthalmologists in detecting and classifying eye diseases.
Vellakani S; Pushbam I
J Xray Sci Technol; 2020; 28(5):975-988. PubMed ID: 32597828
[TBL] [Abstract][Full Text] [Related]
5. OctNET: A Lightweight CNN for Retinal Disease Classification from Optical Coherence Tomography Images.
A P S; Kar S; S G; Gopi VP; Palanisamy P
Comput Methods Programs Biomed; 2021 Mar; 200():105877. PubMed ID: 33339630
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. Attention to Lesion: Lesion-Aware Convolutional Neural Network for Retinal Optical Coherence Tomography Image Classification.
Fang L; Wang C; Li S; Rabbani H; Chen X; Liu Z
IEEE Trans Med Imaging; 2019 Aug; 38(8):1959-1970. PubMed ID: 30763240
[TBL] [Abstract][Full Text] [Related]
8. Classification of optical coherence tomography images using a capsule network.
Tsuji T; Hirose Y; Fujimori K; Hirose T; Oyama A; Saikawa Y; Mimura T; Shiraishi K; Kobayashi T; Mizota A; Kotoku J
BMC Ophthalmol; 2020 Mar; 20(1):114. PubMed ID: 32192460
[TBL] [Abstract][Full Text] [Related]
9. A Hybrid Model Composed of Two Convolutional Neural Networks (CNNs) for Automatic Retinal Layer Segmentation of OCT Images in Retinitis Pigmentosa (RP).
Wang YZ; Wu W; Birch DG
Transl Vis Sci Technol; 2021 Nov; 10(13):9. PubMed ID: 34751740
[TBL] [Abstract][Full Text] [Related]
10. Surrogate-Assisted Retinal OCT Image Classification Based on Convolutional Neural Networks.
Rong Y; Xiang D; Zhu W; Yu K; Shi F; Fan Z; Chen X
IEEE J Biomed Health Inform; 2019 Jan; 23(1):253-263. PubMed ID: 29994378
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Artificial intelligence based detection of age-related macular degeneration using optical coherence tomography with unique image preprocessing.
Celebi ARC; Bulut E; Sezer A
Eur J Ophthalmol; 2023 Jan; 33(1):65-73. PubMed ID: 35469472
[TBL] [Abstract][Full Text] [Related]
13. Segmentation of paracentral acute middle maculopathy lesions in spectral-domain optical coherence tomography images through weakly supervised deep convolutional networks.
Zhang T; Wei Q; Li Z; Meng W; Zhang M; Zhang Z
Comput Methods Programs Biomed; 2023 Oct; 240():107632. PubMed ID: 37329802
[TBL] [Abstract][Full Text] [Related]
14. A new computer-aided diagnosis tool based on deep learning methods for automatic detection of retinal disorders from OCT images.
Alizadeh Eghtedar R; Vard A; Malekahmadi M; Peyman A
Int Ophthalmol; 2024 Feb; 44(1):110. PubMed ID: 38396074
[TBL] [Abstract][Full Text] [Related]
15. Comparison of the proposed DCNN model with standard CNN architectures for retinal diseases classification.
Mohan R; Ganapathy K; Arunmozhi R
J Popul Ther Clin Pharmacol; 2022; 29(3):e112-e122. PubMed ID: 36196946
[TBL] [Abstract][Full Text] [Related]
16. Application of Imaging Examination Based on Deep Learning in the Diagnosis of Viral Senile Pneumonia.
Deng X; Ge X; Xue Q; Liu H
Contrast Media Mol Imaging; 2022; 2022():6964283. PubMed ID: 35694707
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Modular deep neural networks for automatic quality control of retinal optical coherence tomography scans.
Kauer-Bonin J; Yadav SK; Beckers I; Gawlik K; Motamedi S; Zimmermann HG; Kadas EM; Haußer F; Paul F; Brandt AU
Comput Biol Med; 2022 Feb; 141():104822. PubMed ID: 34548173
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. Diagnosis of retinal disorders from Optical Coherence Tomography images using CNN.
Rajagopalan N; N V; Josephraj AN; E S
PLoS One; 2021; 16(7):e0254180. PubMed ID: 34314421
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]