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Fast Optic Disc Segmentation in Retinal Images Using Polar Transform

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Book cover Medical Image Understanding and Analysis (MIUA 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 723))

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Abstract

Glaucoma is one among major causes of blindness. Early detection of glaucoma through automated retinal image analysis helps in preventing vision loss. Optic Disc segmentation from retinal images is considered as the preliminary step in developing the diagnostic tool for early Glaucoma detection. A novel hierarchical technique for optic disc localization and segmentation on retinal fundus images is presented in this paper. Retinal vasculature and pathologies are delineate and removed by using morphological operations as preprocessing steps. Circular Hough transform is used to localize the optic disc. Region of interest is calculated and a novel polar transform based adaptive thresholding is performed to obtain the precise boundary of optic disc. The methodology has shown considerable improvement over existing methods in terms of accuracy and processing time. The algorithm is evaluated on a number of publicly available retinal image sets which includes MESSIDOR, DIARETDB1, DRIONS-DB, HRF, DRIVE and RIM-ONE, with average spatial overlap approximately 85%.

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Authors and Affiliations

  1. School of Electrical Engineering and Computer Science, National University of Sciences and Technology, Islamabad, Pakistan

    Muhammad Nauman Zahoor & Muhammad Moazam Fraz

Authors
  1. Muhammad Nauman Zahoor
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  2. Muhammad Moazam Fraz
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Corresponding author

Correspondence to Muhammad Moazam Fraz .

Editor information

Editors and Affiliations

  1. Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, United Kingdom

    María Valdés Hernández

  2. University of León, León, Spain

    Víctor González-Castro

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Zahoor, M.N., Fraz, M.M. (2017). Fast Optic Disc Segmentation in Retinal Images Using Polar Transform. In: Valdés Hernández, M., González-Castro, V. (eds) Medical Image Understanding and Analysis. MIUA 2017. Communications in Computer and Information Science, vol 723. Springer, Cham. https://doi.org/10.1007/978-3-319-60964-5_4

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  • DOI: https://doi.org/10.1007/978-3-319-60964-5_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60963-8

  • Online ISBN: 978-3-319-60964-5

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