157 related articles for article (PubMed ID: 35141807)
21. Optic disc detection and segmentation using saliency mask in retinal fundus images.
Zaaboub N; Sandid F; Douik A; Solaiman B
Comput Biol Med; 2022 Nov; 150():106067. PubMed ID: 36150251
[TBL] [Abstract][Full Text] [Related]
22. A robust method for the automatic location of the optic disc and the fovea in fundus images.
Romero-Oraá R; García M; Oraá-Pérez J; López MI; Hornero R
Comput Methods Programs Biomed; 2020 Nov; 196():105599. PubMed ID: 32574904
[TBL] [Abstract][Full Text] [Related]
23. Automated image quality appraisal through partial least squares discriminant analysis.
Ramani RG; Shanthamalar JJ
Int J Comput Assist Radiol Surg; 2022 Jul; 17(7):1367-1377. PubMed ID: 35650346
[TBL] [Abstract][Full Text] [Related]
24. Exudate detection in fundus images using deeply-learnable features.
Khojasteh P; Passos Júnior LA; Carvalho T; Rezende E; Aliahmad B; Papa JP; Kumar DK
Comput Biol Med; 2019 Jan; 104():62-69. PubMed ID: 30439600
[TBL] [Abstract][Full Text] [Related]
25. Microaneurysms detection in color fundus images using machine learning based on directional local contrast.
Long S; Chen J; Hu A; Liu H; Chen Z; Zheng D
Biomed Eng Online; 2020 Apr; 19(1):21. PubMed ID: 32295576
[TBL] [Abstract][Full Text] [Related]
26. An exudate detection method for diagnosis risk of diabetic macular edema in retinal images using feature-based and supervised classification.
Marin D; Gegundez-Arias ME; Ponte B; Alvarez F; Garrido J; Ortega C; Vasallo MJ; Bravo JM
Med Biol Eng Comput; 2018 Aug; 56(8):1379-1390. PubMed ID: 29318442
[TBL] [Abstract][Full Text] [Related]
27. Detection of exudates in fundus images using a Markovian segmentation model.
Harangi B; Hajdu A
Annu Int Conf IEEE Eng Med Biol Soc; 2014; 2014():130-3. PubMed ID: 25569914
[TBL] [Abstract][Full Text] [Related]
28. Resilient back-propagation machine learning-based classification on fundus images for retinal microaneurysm detection.
Steffi S; Sam Emmanuel WR
Int Ophthalmol; 2024 Feb; 44(1):91. PubMed ID: 38367192
[TBL] [Abstract][Full Text] [Related]
29. Diagnosis of diabetic retinopathy: automatic extraction of optic disc and exudates from retinal images using marker-controlled watershed transformation.
Reza AW; Eswaran C; Dimyati K
J Med Syst; 2011 Dec; 35(6):1491-501. PubMed ID: 20703768
[TBL] [Abstract][Full Text] [Related]
30. Red-lesion extraction in retinal fundus images by directional intensity changes' analysis.
Monemian M; Rabbani H
Sci Rep; 2021 Sep; 11(1):18223. PubMed ID: 34521886
[TBL] [Abstract][Full Text] [Related]
31. Weighted ensemble based automatic detection of exudates in fundus photographs.
Prentasic P; Loncaric S
Annu Int Conf IEEE Eng Med Biol Soc; 2014; 2014():138-41. PubMed ID: 25569916
[TBL] [Abstract][Full Text] [Related]
32. A novel method for retinal exudate segmentation using signal separation algorithm.
Imani E; Pourreza HR
Comput Methods Programs Biomed; 2016 Sep; 133():195-205. PubMed ID: 27393810
[TBL] [Abstract][Full Text] [Related]
33. A novel four-step feature selection technique for diabetic retinopathy grading.
Jagan Mohan N; Murugan R; Goel T; Mirjalili S; Roy P
Phys Eng Sci Med; 2021 Dec; 44(4):1351-1366. PubMed ID: 34748191
[TBL] [Abstract][Full Text] [Related]
34. Feature extraction and selection for the automatic detection of hard exudates in retinal images.
Garcia M; Hornero R; Sánchez CI; López MI; Diez A
Annu Int Conf IEEE Eng Med Biol Soc; 2007; 2007():4969-72. PubMed ID: 18003122
[TBL] [Abstract][Full Text] [Related]
35. An Automated System for the Detection and Classification of Retinal Changes Due to Red Lesions in Longitudinal Fundus Images.
Adal KM; van Etten PG; Martinez JP; Rouwen KW; Vermeer KA; van Vliet LJ
IEEE Trans Biomed Eng; 2018 Jun; 65(6):1382-1390. PubMed ID: 28922110
[TBL] [Abstract][Full Text] [Related]
36. Hybrid multi-kernel SVM algorithm for detection of microaneurysm in color fundus images.
Derwin DJ; Shan BP; Singh OJ
Med Biol Eng Comput; 2022 May; 60(5):1377-1390. PubMed ID: 35325369
[TBL] [Abstract][Full Text] [Related]
37. Automated lesion detectors in retinal fundus images.
Figueiredo IN; Kumar S; Oliveira CM; Ramos JD; Engquist B
Comput Biol Med; 2015 Nov; 66():47-65. PubMed ID: 26378502
[TBL] [Abstract][Full Text] [Related]
38. Distinguising Proof of Diabetic Retinopathy Detection by Hybrid Approaches in Two Dimensional Retinal Fundus Images.
S K; D M
J Med Syst; 2019 May; 43(6):173. PubMed ID: 31069550
[TBL] [Abstract][Full Text] [Related]
39. EAD-Net: A Novel Lesion Segmentation Method in Diabetic Retinopathy Using Neural Networks.
Wan C; Chen Y; Li H; Zheng B; Chen N; Yang W; Wang C; Li Y
Dis Markers; 2021; 2021():6482665. PubMed ID: 34512815
[TBL] [Abstract][Full Text] [Related]
40. Referral system for hard exudates in eye fundus.
Naqvi SA; Zafar MF; Haq Iu
Comput Biol Med; 2015 Sep; 64():217-35. PubMed ID: 26231313
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]