293 related articles for article (PubMed ID: 32750920)
1. ELEMENT: Multi-Modal Retinal Vessel Segmentation Based on a Coupled Region Growing and Machine Learning Approach.
Rodrigues EO; Conci A; Liatsis P
IEEE J Biomed Health Inform; 2020 Dec; 24(12):3507-3519. PubMed ID: 32750920
[TBL] [Abstract][Full Text] [Related]
2. Hard Attention Net for Automatic Retinal Vessel Segmentation.
Wang D; Haytham A; Pottenburgh J; Saeedi O; Tao Y
IEEE J Biomed Health Inform; 2020 Dec; 24(12):3384-3396. PubMed ID: 32750941
[TBL] [Abstract][Full Text] [Related]
3. Multi-proportion channel ensemble model for retinal vessel segmentation.
Tang P; Liang Q; Yan X; Zhang D; Coppola G; Sun W
Comput Biol Med; 2019 Aug; 111():103352. PubMed ID: 31301636
[TBL] [Abstract][Full Text] [Related]
4. Joint Segment-Level and Pixel-Wise Losses for Deep Learning Based Retinal Vessel Segmentation.
Yan Z; Yang X; Cheng KT
IEEE Trans Biomed Eng; 2018 Sep; 65(9):1912-1923. PubMed ID: 29993396
[TBL] [Abstract][Full Text] [Related]
5. DAVS-NET: Dense Aggregation Vessel Segmentation Network for retinal vasculature detection in fundus images.
Raza M; Naveed K; Akram A; Salem N; Afaq A; Madni HA; Khan MAU; Din MZ
PLoS One; 2021; 16(12):e0261698. PubMed ID: 34972109
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. A Multi-Scale Directional Line Detector for Retinal Vessel Segmentation.
Khawaja A; Khan TM; Khan MAU; Nawaz SJ
Sensors (Basel); 2019 Nov; 19(22):. PubMed ID: 31766276
[TBL] [Abstract][Full Text] [Related]
8. NFN+: A novel network followed network for retinal vessel segmentation.
Wu Y; Xia Y; Song Y; Zhang Y; Cai W
Neural Netw; 2020 Jun; 126():153-162. PubMed ID: 32222424
[TBL] [Abstract][Full Text] [Related]
9. Regional Image Features Model for Automatic Classification between Normal and Glaucoma in Fundus and Scanning Laser Ophthalmoscopy (SLO) Images.
Haleem MS; Han L; Hemert Jv; Fleming A; Pasquale LR; Silva PS; Song BJ; Aiello LP
J Med Syst; 2016 Jun; 40(6):132. PubMed ID: 27086033
[TBL] [Abstract][Full Text] [Related]
10. Robust Content-Adaptive Global Registration for Multimodal Retinal Images Using Weakly Supervised Deep-Learning Framework.
Wang Y; Zhang J; Cavichini M; Bartsch DG; Freeman WR; Nguyen TQ; An C
IEEE Trans Image Process; 2021; 30():3167-3178. PubMed ID: 33600314
[TBL] [Abstract][Full Text] [Related]
11. A Three-Stage Deep Learning Model for Accurate Retinal Vessel Segmentation.
Yan Z; Yang X; Cheng KT
IEEE J Biomed Health Inform; 2019 Jul; 23(4):1427-1436. PubMed ID: 30281503
[TBL] [Abstract][Full Text] [Related]
12. Particle swarm optimization method for small retinal vessels detection on multiresolution fundus images.
Khomri B; Christodoulidis A; Djerou L; Babahenini MC; Cheriet F
J Biomed Opt; 2018 May; 23(5):1-13. PubMed ID: 29749141
[TBL] [Abstract][Full Text] [Related]
13. Retinal Vessel Segmentation, a Review of Classic and Deep Methods.
Khandouzi A; Ariafar A; Mashayekhpour Z; Pazira M; Baleghi Y
Ann Biomed Eng; 2022 Oct; 50(10):1292-1314. PubMed ID: 36008569
[TBL] [Abstract][Full Text] [Related]
14. Accurate Retinal Vessel Segmentation in Color Fundus Images via Fully Attention-Based Networks.
Li K; Qi X; Luo Y; Yao Z; Zhou X; Sun M
IEEE J Biomed Health Inform; 2021 Jun; 25(6):2071-2081. PubMed ID: 33001809
[TBL] [Abstract][Full Text] [Related]
15. Scale-space approximated convolutional neural networks for retinal vessel segmentation.
Noh KJ; Park SJ; Lee S
Comput Methods Programs Biomed; 2019 Sep; 178():237-246. PubMed ID: 31416552
[TBL] [Abstract][Full Text] [Related]
16. Retinal blood vessel extraction employing effective image features and combination of supervised and unsupervised machine learning methods.
Hashemzadeh M; Adlpour Azar B
Artif Intell Med; 2019 Apr; 95():1-15. PubMed ID: 30904129
[TBL] [Abstract][Full Text] [Related]
17. Supervised retinal vessel segmentation from color fundus images based on matched filtering and AdaBoost classifier.
Memari N; Ramli AR; Bin Saripan MI; Mashohor S; Moghbel M
PLoS One; 2017; 12(12):e0188939. PubMed ID: 29228036
[TBL] [Abstract][Full Text] [Related]
18. A location-to-segmentation strategy for automatic exudate segmentation in colour retinal fundus images.
Liu Q; Zou B; Chen J; Ke W; Yue K; Chen Z; Zhao G
Comput Med Imaging Graph; 2017 Jan; 55():78-86. PubMed ID: 27665058
[TBL] [Abstract][Full Text] [Related]
19. A Global and Local Enhanced Residual U-Net for Accurate Retinal Vessel Segmentation.
Lian S; Li L; Lian G; Xiao X; Luo Z; Li S
IEEE/ACM Trans Comput Biol Bioinform; 2021; 18(3):852-862. PubMed ID: 31095493
[TBL] [Abstract][Full Text] [Related]
20. A novel retinal vessel detection approach based on multiple deep convolution neural networks.
Guo Y; Budak Ü; Şengür A
Comput Methods Programs Biomed; 2018 Dec; 167():43-48. PubMed ID: 30501859
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]