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Journal Abstract Search

330 related items for PubMed ID: 29090844

  • 1. Computer-aided diagnosis based on enhancement of degraded fundus photographs.
    Jin K, Zhou M, Wang S, Lou L, Xu Y, Ye J, Qian D.
    Acta Ophthalmol; 2018 May; 96(3):e320-e326. PubMed ID: 29090844
    [Abstract] [Full Text] [Related]

  • 2. Automated retinal health diagnosis using pyramid histogram of visual words and Fisher vector techniques.
    Koh JEW, Ng EYK, Bhandary SV, Hagiwara Y, Laude A, Acharya UR.
    Comput Biol Med; 2018 Jan 01; 92():204-209. PubMed ID: 29227822
    [Abstract] [Full Text] [Related]

  • 3. Imperceptible watermarking for security of fundus images in tele-ophthalmology applications and computer-aided diagnosis of retina diseases.
    Singh A, Dutta MK.
    Int J Med Inform; 2017 Dec 01; 108():110-124. PubMed ID: 29132616
    [Abstract] [Full Text] [Related]

  • 4. Color Retinal Image Enhancement Based on Luminosity and Contrast Adjustment.
    Zhou M, Jin K, Wang S, Ye J, Qian D.
    IEEE Trans Biomed Eng; 2018 Mar 01; 65(3):521-527. PubMed ID: 28475043
    [Abstract] [Full Text] [Related]

  • 5. Automatic computer-aided analysis of optic disc pallor in fundus photographs.
    Yang HK, Oh JE, Han SB, Kim KG, Hwang JM.
    Acta Ophthalmol; 2019 Jun 01; 97(4):e519-e525. PubMed ID: 30407733
    [Abstract] [Full Text] [Related]

  • 6. Diagnosis of retinal health in digital fundus images using continuous wavelet transform (CWT) and entropies.
    Koh JEW, Acharya UR, Hagiwara Y, Raghavendra U, Tan JH, Sree SV, Bhandary SV, Rao AK, Sivaprasad S, Chua KC, Laude A, Tong L.
    Comput Biol Med; 2017 May 01; 84():89-97. PubMed ID: 28351716
    [Abstract] [Full Text] [Related]

  • 7. Fundus Image Enhancement Method Based on CycleGAN.
    You Q, Wan C, Sun J, Shen J, Ye H, Yu Q.
    Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul 01; 2019():4500-4503. PubMed ID: 31946865
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  • 9. Retinal image enhancement based on color dominance of image.
    C P, R JK.
    Sci Rep; 2023 May 03; 13(1):7172. PubMed ID: 37138000
    [Abstract] [Full Text] [Related]

  • 10. [A new approach for studying the retinal and choroidal circulation].
    Yoneya S.
    Nippon Ganka Gakkai Zasshi; 2004 Dec 03; 108(12):836-61; discussion 862. PubMed ID: 15656089
    [Abstract] [Full Text] [Related]

  • 11. Enhancement and restoration of non-uniform illuminated Fundus Image of Retina obtained through thin layer of cataract.
    Mitra A, Roy S, Roy S, Setua SK.
    Comput Methods Programs Biomed; 2018 Mar 03; 156():169-178. PubMed ID: 29428069
    [Abstract] [Full Text] [Related]

  • 12. Automatic fundus image classification for computer-aided diagonsis.
    Lu S, Liu J, Lim JH, Zhang Z, Meng TN, Wong WK, Li H, Wong TY.
    Annu Int Conf IEEE Eng Med Biol Soc; 2009 Mar 03; 2009():1453-6. PubMed ID: 19963750
    [Abstract] [Full Text] [Related]

  • 13. Recent trends and advances in fundus image analysis: A review.
    Iqbal S, Khan TM, Naveed K, Naqvi SS, Nawaz SJ.
    Comput Biol Med; 2022 Dec 03; 151(Pt A):106277. PubMed ID: 36370579
    [Abstract] [Full Text] [Related]

  • 14. Automated Quality Assessment of Colour Fundus Images for Diabetic Retinopathy Screening in Telemedicine.
    Saha SK, Fernando B, Cuadros J, Xiao D, Kanagasingam Y.
    J Digit Imaging; 2018 Dec 03; 31(6):869-878. PubMed ID: 29704086
    [Abstract] [Full Text] [Related]

  • 15. 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 03; 40(2):124-37. PubMed ID: 20045104
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  • 17. Automatic computer-aided diagnosis of retinal nerve fiber layer defects using fundus photographs in optic neuropathy.
    Oh JE, Yang HK, Kim KG, Hwang JM.
    Invest Ophthalmol Vis Sci; 2015 May 03; 56(5):2872-9. PubMed ID: 25813996
    [Abstract] [Full Text] [Related]

  • 18. Update on wide- and ultra-widefield retinal imaging.
    Shoughy SS, Arevalo JF, Kozak I.
    Indian J Ophthalmol; 2015 Jul 03; 63(7):575-81. PubMed ID: 26458474
    [Abstract] [Full Text] [Related]

  • 19. Development and Validation of Deep Learning Models for Screening Multiple Abnormal Findings in Retinal Fundus Images.
    Son J, Shin JY, Kim HD, Jung KH, Park KH, Park SJ.
    Ophthalmology; 2020 Jan 03; 127(1):85-94. PubMed ID: 31281057
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