These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

110 related articles for article (PubMed ID: 23366169)

  • 1. Efficient optic cup localization using regional propagation based on retinal structure priors.
    Xu Y; Liu J; Cheng J; Yin F; Tan NM; Wong DW; Baskaran M; Cheng CY; Wong TY
    Annu Int Conf IEEE Eng Med Biol Soc; 2012; 2012():1430-3. PubMed ID: 23366169
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Efficient optic cup detection from intra-image learning with retinal structure priors.
    Xu Y; Liu J; Lin S; Xu D; Cheung CY; Aung T; Wong TY
    Med Image Comput Comput Assist Interv; 2012; 15(Pt 1):58-65. PubMed ID: 23285535
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Sliding window and regression based cup detection in digital fundus images for glaucoma diagnosis.
    Xu Y; Xu D; Lin S; Liu J; Cheng J; Cheung CY; Aung T; Wong TY
    Med Image Comput Comput Assist Interv; 2011; 14(Pt 3):1-8. PubMed ID: 22003677
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. 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]  

  • 6. 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]  

  • 7. 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]  

  • 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. Joint optic disc and cup segmentation using semi-supervised conditional GANs.
    Liu S; Hong J; Lu X; Jia X; Lin Z; Zhou Y; Liu Y; Zhang H
    Comput Biol Med; 2019 Dec; 115():103485. PubMed ID: 31630029
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Local patch reconstruction framework for optic cup localization in glaucoma detection.
    Xu Y; Quan Y; Huang Y; Tan NM; Li R; Duan L; Chen L; Liu H; Chen X; Wong DW; Baskaran M; Perera S; Aung T; Wong TY; Liu J
    Annu Int Conf IEEE Eng Med Biol Soc; 2014; 2014():5418-21. PubMed ID: 25571219
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Learning-based approach for the automatic detection of the optic disc in digital retinal fundus photographs.
    Wong DK; Liu J; Tan NM; Yin F; Lee BH; Wong TY
    Annu Int Conf IEEE Eng Med Biol Soc; 2010; 2010():5355-8. PubMed ID: 21096259
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Direct Cup-to-Disc Ratio Estimation for Glaucoma Screening via Semi-Supervised Learning.
    Zhao R; Chen X; Liu X; Chen Z; Guo F; Li S
    IEEE J Biomed Health Inform; 2020 Apr; 24(4):1104-1113. PubMed ID: 31403451
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Segmentation of the blood vessels and optic disk in retinal images.
    Salazar-Gonzalez A; Kaba D; Li Y; Liu X
    IEEE J Biomed Health Inform; 2014 Nov; 18(6):1874-86. PubMed ID: 25265617
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Superpixel classification for initialization in model based optic disc segmentation.
    Cheng J; Liu J; Xu Y; Yin F; Wong DW; Lee BH; Cheung C; Aung T; Wong TY
    Annu Int Conf IEEE Eng Med Biol Soc; 2012; 2012():1450-3. PubMed ID: 23366174
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. Robust multi-scale superpixel classification for optic cup localization.
    Tan NM; Xu Y; Goh WB; Liu J
    Comput Med Imaging Graph; 2015 Mar; 40():182-93. PubMed ID: 25453464
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. 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]  

  • 19. Fully Convolutional Networks for Monocular Retinal Depth Estimation and Optic Disc-Cup Segmentation.
    Shankaranarayana SM; Ram K; Mitra K; Sivaprakasam M
    IEEE J Biomed Health Inform; 2019 Jul; 23(4):1417-1426. PubMed ID: 30762573
    [TBL] [Abstract][Full Text] [Related]  

  • 20. ORIGA(-light): an online retinal fundus image database for glaucoma analysis and research.
    Zhang Z; Yin FS; Liu J; Wong WK; Tan NM; Lee BH; Cheng J; Wong TY
    Annu Int Conf IEEE Eng Med Biol Soc; 2010; 2010():3065-8. PubMed ID: 21095735
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.