Literature DB >> 12585705

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

Thomas Walter1, Jean-Claude Klein, Pascale Massin, Ali Erginay.   

Abstract

In the framework of computer assisted diagnosis of diabetic retinopathy, a new algorithm for detection of exudates is presented and discussed. The presence of exudates within the macular region is a main hallmark of diabetic macular edema and allows its detection with a high sensitivity. Hence, detection of exudates is an important diagnostic task, in which computer assistance may play a major role. Exudates are found using their high grey level variation, and their contours are determined by means of morphological reconstruction techniques. The detection of the optic disc is indispensable for this approach. We detect the optic disc by means of morphological filtering techniques and the watershed transformation. The algorithm has been tested on a small image data base and compared with the performance of a human grader. As a result, we obtain a mean sensitivity of 92.8% and a mean predictive value of 92.4%. Robustness with respect to changes of the parameters of the algorithm has been evaluated.

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Mesh:

Year:  2002        PMID: 12585705     DOI: 10.1109/TMI.2002.806290

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  56 in total

1.  Analysis of retinal fundus images for grading of diabetic retinopathy severity.

Authors:  M H Ahmad Fadzil; Lila Iznita Izhar; Hermawan Nugroho; Hanung Adi Nugroho
Journal:  Med Biol Eng Comput       Date:  2011-01-27       Impact factor: 2.602

2.  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

3.  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

4.  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 5.  Retinal imaging and image analysis.

Authors:  Michael D Abràmoff; Mona K Garvin; Milan Sonka
Journal:  IEEE Rev Biomed Eng       Date:  2010

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

Authors:  Ahmed Wasif Reza; C Eswaran; Subhas Hati
Journal:  J Med Syst       Date:  2009-02       Impact factor: 4.460

Review 7.  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

8.  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

9.  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

10.  Automated detection and grading of diabetic maculopathy in digital retinal images.

Authors:  Anam Tariq; M Usman Akram; Arslan Shaukat; Shoab A Khan
Journal:  J Digit Imaging       Date:  2013-08       Impact factor: 4.056

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