396 related articles for article (PubMed ID: 27764542)
1. Optic cup segmentation from fundus images for glaucoma diagnosis.
Hu M; Zhu C; Li X; Xu Y
Bioengineered; 2017 Jan; 8(1):21-28. PubMed ID: 27764542
[TBL] [Abstract][Full Text] [Related]
2. Optic disk and cup segmentation from monocular color retinal images for glaucoma assessment.
Joshi GD; Sivaswamy J; Krishnadas SR
IEEE Trans Med Imaging; 2011 Jun; 30(6):1192-205. PubMed ID: 21536531
[TBL] [Abstract][Full Text] [Related]
3. Joint optic disc and cup boundary extraction from monocular fundus images.
Chakravarty A; Sivaswamy J
Comput Methods Programs Biomed; 2017 Aug; 147():51-61. PubMed ID: 28734530
[TBL] [Abstract][Full Text] [Related]
4. An automated and robust image processing algorithm for glaucoma diagnosis from fundus images using novel blood vessel tracking and bend point detection.
M S; Issac A; Dutta MK
Int J Med Inform; 2018 Feb; 110():52-70. PubMed ID: 29331255
[TBL] [Abstract][Full Text] [Related]
5. Sector-based optic cup segmentation with intensity and blood vessel priors.
Yin F; Liu J; Wong DW; Tan NM; Cheng J; Cheng CY; Tham YC; Wong TY
Annu Int Conf IEEE Eng Med Biol Soc; 2012; 2012():1454-7. PubMed ID: 23366175
[TBL] [Abstract][Full Text] [Related]
6. Superpixel classification based optic disc and optic cup segmentation for glaucoma screening.
Cheng J; Liu J; Xu Y; Yin F; Wong DW; Tan NM; Tao D; Cheng CY; Aung T; Wong TY
IEEE Trans Med Imaging; 2013 Jun; 32(6):1019-32. PubMed ID: 23434609
[TBL] [Abstract][Full Text] [Related]
7. An adaptive threshold based image processing technique for improved glaucoma detection and classification.
Issac A; Partha Sarathi M; Dutta MK
Comput Methods Programs Biomed; 2015 Nov; 122(2):229-44. PubMed ID: 26321351
[TBL] [Abstract][Full Text] [Related]
8. Segmentation of optic disc and optic cup in retinal fundus images using shape regression.
Sedai S; Roy PK; Mahapatra D; Garnavi R
Annu Int Conf IEEE Eng Med Biol Soc; 2016 Aug; 2016():3260-3264. PubMed ID: 28269003
[TBL] [Abstract][Full Text] [Related]
9. Automated determination of cup-to-disc ratio for classification of glaucomatous and normal eyes on stereo retinal fundus images.
Muramatsu C; Nakagawa T; Sawada A; Hatanaka Y; Yamamoto T; Fujita H
J Biomed Opt; 2011 Sep; 16(9):096009. PubMed ID: 21950923
[TBL] [Abstract][Full Text] [Related]
10. Fully automated method for glaucoma screening using robust optic nerve head detection and unsupervised segmentation based cup-to-disc ratio computation in retinal fundus images.
Mvoulana A; Kachouri R; Akil M
Comput Med Imaging Graph; 2019 Oct; 77():101643. PubMed ID: 31541937
[TBL] [Abstract][Full Text] [Related]
11. Multimodal retinal image registration for optic disk segmentation.
Chrástek R; Skokan M; Kubecka L; Wolf M; Donath K; Jan J; Michelson G; Niemann H
Methods Inf Med; 2004; 43(4):336-42. PubMed ID: 15472744
[TBL] [Abstract][Full Text] [Related]
12. Superpixel classification based optic cup segmentation.
Cheng J; Liu J; Tao D; Yin F; Wong DW; Xu Y; Wong TY
Med Image Comput Comput Assist Interv; 2013; 16(Pt 3):421-8. PubMed ID: 24505789
[TBL] [Abstract][Full Text] [Related]
13. Level-set based automatic cup-to-disc ratio determination using retinal fundus images in ARGALI.
Wong DK; Liu J; Lim JH; Jia X; Yin F; Li H; Wong TY
Annu Int Conf IEEE Eng Med Biol Soc; 2008; 2008():2266-9. PubMed ID: 19163151
[TBL] [Abstract][Full Text] [Related]
14. Segmentation of the optic disk in color eye fundus images using an adaptive morphological approach.
Welfer D; Scharcanski J; Kitamura CM; Dal Pizzol MM; Ludwig LW; Marinho DR
Comput Biol Med; 2010 Feb; 40(2):124-37. PubMed ID: 20045104
[TBL] [Abstract][Full Text] [Related]
15. Improved automated optic cup segmentation based on detection of blood vessel bends in retinal fundus images.
Hatanaka Y; Nagahata Y; Muramatsu C; Okumura S; Ogohara K; Sawada A; Ishida K; Yamamoto T; Fujita H
Annu Int Conf IEEE Eng Med Biol Soc; 2014; 2014():126-9. PubMed ID: 25569913
[TBL] [Abstract][Full Text] [Related]
16. Optic disc and optic cup segmentation based on anatomy guided cascade network.
Bian X; Luo X; Wang C; Liu W; Lin X
Comput Methods Programs Biomed; 2020 Dec; 197():105717. PubMed ID: 32957060
[TBL] [Abstract][Full Text] [Related]
17. Variance owing to observer, repeat imaging, and fundus camera type on cup-to-disc ratio estimates by stereo planimetry.
Kwon YH; Adix M; Zimmerman MB; Piette S; Greenlee EC; Alward WL; Abràmoff MD
J Glaucoma; 2009; 18(4):305-10. PubMed ID: 19365196
[TBL] [Abstract][Full Text] [Related]
18. An ensembling approach for optic cup detection based on spatial heuristic analysis in retinal fundus images.
Wong DW; Liu J; Tan NM; Fengshou Y; Cheung C; Baskaran M; Aung T; Wong TY
Annu Int Conf IEEE Eng Med Biol Soc; 2012; 2012():1426-9. PubMed ID: 23366168
[TBL] [Abstract][Full Text] [Related]
19. Optic Disc and Cup Segmentation with Blood Vessel Removal from Fundus Images for Glaucoma Detection.
Jiang Y; Xia H; Xu Y; Cheng J; Fu H; Duan L; Meng Z; Liu J
Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():862-865. PubMed ID: 30440527
[TBL] [Abstract][Full Text] [Related]
20. A Unified Optic Nerve Head and Optic Cup Segmentation Using Unsupervised Neural Networks for Glaucoma Screening.
Ghassabi Z; Shanbehzadeh J; Nouri-Mahdavi K
Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():5942-5945. PubMed ID: 30441689
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
