Literature DB >> 19238899

Automatic tracing of optic disc and exudates from color fundus images using fixed and variable thresholds.

Ahmed Wasif Reza1, C Eswaran, Subhas Hati.   

Abstract

The detection of bright objects such as optic disc (OD) and exudates in color fundus images is an important step in the diagnosis of eye diseases such as diabetic retinopathy and glaucoma. In this paper, a novel approach to automatically segment the OD and exudates is proposed. The proposed algorithm makes use of the green component of the image and preprocessing steps such as average filtering, contrast adjustment, and thresholding. The other processing techniques used are morphological opening, extended maxima operator, minima imposition, and watershed transformation. The proposed algorithm is evaluated using the test images of STARE and DRIVE databases with fixed and variable thresholds. The images drawn by human expert are taken as the reference images. The proposed method yields sensitivity values as high as 96.7%, which are better than the results reported in the literature.

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Year:  2009        PMID: 19238899     DOI: 10.1007/s10916-008-9166-4

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  8 in total

1.  Automated localisation of the optic disc, fovea, and retinal blood vessels from digital colour fundus images.

Authors:  C Sinthanayothin; J F Boyce; H L Cook; T H Williamson
Journal:  Br J Ophthalmol       Date:  1999-08       Impact factor: 4.638

2.  A contribution of image processing to the diagnosis of diabetic retinopathy--detection of exudates in color fundus images of the human retina.

Authors:  Thomas Walter; Jean-Claude Klein; Pascale Massin; Ali Erginay
Journal:  IEEE Trans Med Imaging       Date:  2002-10       Impact factor: 10.048

3.  Automated feature extraction in color retinal images by a model based approach.

Authors:  Huiqi Li; Opas Chutatape
Journal:  IEEE Trans Biomed Eng       Date:  2004-02       Impact factor: 4.538

4.  Segmentation of the optic disc, macula and vascular arch in fundus photographs.

Authors:  Meindert Niemeijer; Michael D Abràmoff; Bram van Ginneken
Journal:  IEEE Trans Med Imaging       Date:  2007-01       Impact factor: 10.048

5.  Segmentation of retinal blood vessels by combining the detection of centerlines and morphological reconstruction.

Authors:  Ana Maria Mendonça; Aurélio Campilho
Journal:  IEEE Trans Med Imaging       Date:  2006-09       Impact factor: 10.048

6.  Registration of new blindness in Singapore for 1985-1995.

Authors:  K H Lim
Journal:  Singapore Med J       Date:  1998-03       Impact factor: 1.858

7.  Image analysis of fundus photographs. The detection and measurement of exudates associated with diabetic retinopathy.

Authors:  N P Ward; S Tomlinson; C J Taylor
Journal:  Ophthalmology       Date:  1989-01       Impact factor: 12.079

8.  Automated detection and quantification of retinal exudates.

Authors:  R Phillips; J Forrester; P Sharp
Journal:  Graefes Arch Clin Exp Ophthalmol       Date:  1993-02       Impact factor: 3.117

  8 in total
  13 in total

1.  An approach to identify optic disc in human retinal images using ant colony optimization method.

Authors:  Ganesan Kavitha; Swaminathan Ramakrishnan
Journal:  J Med Syst       Date:  2009-04-28       Impact factor: 4.460

2.  Diagnosis of diabetic retinopathy: automatic extraction of optic disc and exudates from retinal images using marker-controlled watershed transformation.

Authors:  Ahmed Wasif Reza; C Eswaran; Kaharudin Dimyati
Journal:  J Med Syst       Date:  2010-01-29       Impact factor: 4.460

3.  A decision support system for automatic screening of non-proliferative diabetic retinopathy.

Authors:  Ahmed Wasif Reza; C Eswaran
Journal:  J Med Syst       Date:  2009-07-04       Impact factor: 4.460

Review 4.  Optic disc detection in retinal fundus images using gravitational law-based edge detection.

Authors:  Mohammad Alshayeji; Suood Abdulaziz Al-Roomi; Sa'ed Abed
Journal:  Med Biol Eng Comput       Date:  2016-09-16       Impact factor: 2.602

5.  Automated identification of exudates and optic disc based on inverse surface thresholding.

Authors:  Haniza Yazid; Hamzah Arof; Hazlita Mohd Isa
Journal:  J Med Syst       Date:  2011-02-12       Impact factor: 4.460

6.  A new approach to optic disc detection in human retinal images using the firefly algorithm.

Authors:  Javad Rahebi; Fırat Hardalaç
Journal:  Med Biol Eng Comput       Date:  2015-06-21       Impact factor: 2.602

7.  Investigations of severity level measurements for diabetic macular oedema using machine learning algorithms.

Authors:  S Murugeswari; R Sukanesh
Journal:  Ir J Med Sci       Date:  2017-05-15       Impact factor: 1.568

8.  A new blood vessel extraction technique using edge enhancement and object classification.

Authors:  Shahriar Badsha; Ahmed Wasif Reza; Kim Geok Tan; Kaharudin Dimyati
Journal:  J Digit Imaging       Date:  2013-12       Impact factor: 4.056

9.  Computer assisted diagnostic system in tumor radiography.

Authors:  Ahmed Faisal; Sharmin Parveen; Shahriar Badsha; Hasan Sarwar; Ahmed Wasif Reza
Journal:  J Med Syst       Date:  2013-03-17       Impact factor: 4.460

10.  Optic disc detection in color fundus images using ant colony optimization.

Authors:  Carla Pereira; Luís Gonçalves; Manuel Ferreira
Journal:  Med Biol Eng Comput       Date:  2012-11-19       Impact factor: 2.602

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