BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

296 related articles for article (PubMed ID: 27086033)

  • 1. Regional Image Features Model for Automatic Classification between Normal and Glaucoma in Fundus and Scanning Laser Ophthalmoscopy (SLO) Images.
    Haleem MS; Han L; Hemert Jv; Fleming A; Pasquale LR; Silva PS; Song BJ; Aiello LP
    J Med Syst; 2016 Jun; 40(6):132. PubMed ID: 27086033
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning.
    Bajwa MN; Malik MI; Siddiqui SA; Dengel A; Shafait F; Neumeier W; Ahmed S
    BMC Med Inform Decis Mak; 2019 Jul; 19(1):136. PubMed ID: 31315618
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Computer-aided diagnosis of glaucoma using fundus images: A review.
    Hagiwara Y; Koh JEW; Tan JH; Bhandary SV; Laude A; Ciaccio EJ; Tong L; Acharya UR
    Comput Methods Programs Biomed; 2018 Oct; 165():1-12. PubMed ID: 30337064
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. Image processing based automatic diagnosis of glaucoma using wavelet features of segmented optic disc from fundus image.
    Singh A; Dutta MK; ParthaSarathi M; Uher V; Burget R
    Comput Methods Programs Biomed; 2016 Feb; 124():108-20. PubMed ID: 26574297
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Glaucoma detection using novel optic disc localization, hybrid feature set and classification techniques.
    Akram MU; Tariq A; Khalid S; Javed MY; Abbas S; Yasin UU
    Australas Phys Eng Sci Med; 2015 Dec; 38(4):643-55. PubMed ID: 26399880
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Retinal area detector from scanning laser ophthalmoscope (SLO) images for diagnosing retinal diseases.
    Haleem MS; Han L; van Hemert J; Li B; Fleming A
    IEEE J Biomed Health Inform; 2015 Jul; 19(4):1472-82. PubMed ID: 25167560
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 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. 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]  

  • 12. AMD-GAN: Attention encoder and multi-branch structure based generative adversarial networks for fundus disease detection from scanning laser ophthalmoscopy images.
    Xie H; Lei H; Zeng X; He Y; Chen G; Elazab A; Yue G; Wang J; Zhang G; Lei B
    Neural Netw; 2020 Dec; 132():477-490. PubMed ID: 33039786
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Automated vertical cup-to-disc ratio determination from fundus images for glaucoma detection.
    Gao XR; Wu F; Yuhas PT; Rasel RK; Chiariglione M
    Sci Rep; 2024 Feb; 14(1):4494. PubMed ID: 38396048
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Automatic tracing of optic disc and exudates from color fundus images using fixed and variable thresholds.
    Reza AW; Eswaran C; Hati S
    J Med Syst; 2009 Feb; 33(1):73-80. PubMed ID: 19238899
    [TBL] [Abstract][Full Text] [Related]  

  • 15. State-of-the-Art Techniques in Optic Cup and Disc Localization for Glaucoma Diagnosis: Research Results and Issues.
    Balasubramanian K; Ananthamoorthy NP
    Crit Rev Biomed Eng; 2020; 48(1):63-83. PubMed ID: 32749119
    [TBL] [Abstract][Full Text] [Related]  

  • 16. ELEMENT: Multi-Modal Retinal Vessel Segmentation Based on a Coupled Region Growing and Machine Learning Approach.
    Rodrigues EO; Conci A; Liatsis P
    IEEE J Biomed Health Inform; 2020 Dec; 24(12):3507-3519. PubMed ID: 32750920
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. A Novel Adaptive Deformable Model for Automated Optic Disc and Cup Segmentation to Aid Glaucoma Diagnosis.
    Haleem MS; Han L; Hemert JV; Li B; Fleming A; Pasquale LR; Song BJ
    J Med Syst; 2017 Dec; 42(1):20. PubMed ID: 29218460
    [TBL] [Abstract][Full Text] [Related]  

  • 19. An enhanced deep image model for glaucoma diagnosis using feature-based detection in retinal fundus.
    Singh LK; Pooja ; Garg H; Khanna M; Bhadoria RS
    Med Biol Eng Comput; 2021 Feb; 59(2):333-353. PubMed ID: 33439453
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Adaptive weighted locality-constrained sparse coding for glaucoma diagnosis.
    Zhou W; Yi Y; Bao J; Wang W
    Med Biol Eng Comput; 2019 Sep; 57(9):2055-2067. PubMed ID: 31352661
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 15.