BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

278 related articles for article (PubMed ID: 17950655)

  • 1. Automatic detection of microaneurysms in color fundus images.
    Walter T; Massin P; Erginay A; Ordonez R; Jeulin C; Klein JC
    Med Image Anal; 2007 Dec; 11(6):555-66. PubMed ID: 17950655
    [TBL] [Abstract][Full Text] [Related]  

  • 2. [Automatic detection of microaneurysms in colour fundus images].
    Jiménez S; Alemany P; Núñez Benjumea F; Serrano C; Acha B; Fondón I; Carral F; Sánchez C
    Arch Soc Esp Oftalmol; 2011 Sep; 86(9):277-81. PubMed ID: 21893260
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Evaluation of automated fundus photograph analysis algorithms for detecting microaneurysms, haemorrhages and exudates, and of a computer-assisted diagnostic system for grading diabetic retinopathy.
    Dupas B; Walter T; Erginay A; Ordonez R; Deb-Joardar N; Gain P; Klein JC; Massin P
    Diabetes Metab; 2010 Jun; 36(3):213-20. PubMed ID: 20219404
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A novel automatic image processing algorithm for detection of hard exudates based on retinal image analysis.
    Sánchez CI; Hornero R; López MI; Aboy M; Poza J; Abásolo D
    Med Eng Phys; 2008 Apr; 30(3):350-7. PubMed ID: 17556004
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A fully automated comparative microaneurysm digital detection system.
    Cree MJ; Olson JA; McHardy KC; Sharp PF; Forrester JV
    Eye (Lond); 1997; 11 ( Pt 5)():622-8. PubMed ID: 9474307
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A successive clutter-rejection-based approach for early detection of diabetic retinopathy.
    Ram K; Joshi GD; Sivaswamy J
    IEEE Trans Biomed Eng; 2011 Mar; 58(3):664-73. PubMed ID: 21134810
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A computational-intelligence-based approach for detection of exudates in diabetic retinopathy images.
    Osareh A; Shadgar B; Markham R
    IEEE Trans Inf Technol Biomed; 2009 Jul; 13(4):535-45. PubMed ID: 19586814
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Simple hybrid method for fine microaneurysm detection from non-dilated diabetic retinopathy retinal images.
    Sopharak A; Uyyanonvara B; Barman S
    Comput Med Imaging Graph; 2013; 37(5-6):394-402. PubMed ID: 23777979
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Computer classification of nonproliferative diabetic retinopathy.
    Lee SC; Lee ET; Wang Y; Klein R; Kingsley RM; Warn A
    Arch Ophthalmol; 2005 Jun; 123(6):759-64. PubMed ID: 15955976
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Optic disc detection from normalized digital fundus images by means of a vessels' direction matched filter.
    Youssif AR; Ghalwash AZ; Ghoneim AR
    IEEE Trans Med Imaging; 2008 Jan; 27(1):11-8. PubMed ID: 18270057
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Evaluation of the effect of JPEG and JPEG2000 image compression on the detection of diabetic retinopathy.
    Conrath J; Erginay A; Giorgi R; Lecleire-Collet A; Vicaut E; Klein JC; Gaudric A; Massin P
    Eye (Lond); 2007 Apr; 21(4):487-93. PubMed ID: 16456597
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Automated detection of fundus photographic red lesions in diabetic retinopathy.
    Larsen M; Godt J; Larsen N; Lund-Andersen H; Sjølie AK; Agardh E; Kalm H; Grunkin M; Owens DR
    Invest Ophthalmol Vis Sci; 2003 Feb; 44(2):761-6. PubMed ID: 12556411
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Computer-assisted microaneurysm turnover in the early stages of diabetic retinopathy.
    Bernardes R; Nunes S; Pereira I; Torrent T; Rosa A; Coelho D; Cunha-Vaz J
    Ophthalmologica; 2009; 223(5):284-91. PubMed ID: 19372722
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Optimal filter framework for automated, instantaneous detection of lesions in retinal images.
    Quellec G; Russell SR; Abramoff MD
    IEEE Trans Med Imaging; 2011 Feb; 30(2):523-33. PubMed ID: 21292586
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Automated detection of diabetic retinopathy in a fundus photographic screening population.
    Larsen N; Godt J; Grunkin M; Lund-Andersen H; Larsen M
    Invest Ophthalmol Vis Sci; 2003 Feb; 44(2):767-71. PubMed ID: 12556412
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Retinopathy online challenge: automatic detection of microaneurysms in digital color fundus photographs.
    Niemeijer M; van Ginneken B; Cree MJ; Mizutani A; Quellec G; Sanchez CI; Zhang B; Hornero R; Lamard M; Muramatsu C; Wu X; Cazuguel G; You J; Mayo A; Li Q; Hatanaka Y; Cochener B; Roux C; Karray F; Garcia M; Fujita H; Abramoff MD
    IEEE Trans Med Imaging; 2010 Jan; 29(1):185-95. PubMed ID: 19822469
    [TBL] [Abstract][Full Text] [Related]  

  • 17. An automated microaneurysm detector as a tool for identification of diabetic retinopathy in rural optometric practice.
    Jelinek HJ; Cree MJ; Worsley D; Luckie A; Nixon P
    Clin Exp Optom; 2006 Sep; 89(5):299-305. PubMed ID: 16907667
    [TBL] [Abstract][Full Text] [Related]  

  • 18. [Automated detection of microaneurysms by using region growing and Fuzzy Artmap neural network].
    Jiménez S; Alemany P; Núñez FJ; Fondón I; Serrano C; Acha B; Failde I
    Arch Soc Esp Oftalmol; 2012 Sep; 87(9):284-9. PubMed ID: 22824647
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Automated microaneurysm detection using local contrast normalization and local vessel detection.
    Fleming AD; Philip S; Goatman KA; Olson JA; Sharp PF
    IEEE Trans Med Imaging; 2006 Sep; 25(9):1223-32. PubMed ID: 16967807
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A method to assist in the diagnosis of early diabetic retinopathy: Image processing applied to detection of microaneurysms in fundus images.
    Rosas-Romero R; Martínez-Carballido J; Hernández-Capistrán J; Uribe-Valencia LJ
    Comput Med Imaging Graph; 2015 Sep; 44():41-53. PubMed ID: 26245720
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.