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Comparison of machine learning and traditional classifiers in glaucoma diagnosis.

, , , , , and . IEEE Trans. Biomed. Engineering, 49 (9): 963-974 (2002)

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Automated measurement of retinal vascular tortuosity., , , , and . AMIA, AMIA, (1997)Content-based retrieval of ophthalmological images., , , , , , and . ICIP (3), page 703-706. IEEE Computer Society, (1996)Locating Blood Vessels in Retinal Images by Piece-wise Threshold Probing of a Matched Filter Response., , and . IEEE Trans. Med. Imaging, 19 (3): 203-210 (2000)Detecting glaucomatous change in visual fields: Analysis with an optimization framework., , , , , , , , , and 1 other author(s). Journal of Biomedical Informatics, (2015)Luminosity and contrast normalization in color retinal images based on standard reference image., , , and . Medical Imaging: Image Processing, volume 9784 of SPIE Proceedings, page 97843N. SPIE, (2016)A Bayesian network based sequential inference for diagnosis of diseases from retinal images., , and . Pattern Recognition Letters, 26 (4): 459-470 (2005)Fuzzy Convergence., and . CVPR, page 716-721. IEEE Computer Society, (1998)Learning From Data: Recognizing Glaucomatous Defect Patterns and Detecting Progression From Visual Field Measurements., , , , , , , , and . IEEE Trans. Biomed. Engineering, 61 (7): 2112-2124 (2014)Image Database Assisted Classification., , , , , and . VISUAL, volume 1614 of Lecture Notes in Computer Science, page 727-734. Springer, (1999)Locating blood vessels in retinal images by piece-wise threshold probing of a matched filter response., , and . AMIA, AMIA, (1998)