CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Exudates Detection with DBSCAN clustering and Back Propagation Neural Network

by Shantala Giraddi, Jagadeesh Pujari, Shraddha Giraddi
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 86 - Number 19
Year of Publication: 2014
Authors: Shantala Giraddi, Jagadeesh Pujari, Shraddha Giraddi
10.5120/15103-2747

Shantala Giraddi, Jagadeesh Pujari, Shraddha Giraddi . Exudates Detection with DBSCAN clustering and Back Propagation Neural Network. International Journal of Computer Applications. 86, 19 ( January 2014), 16-20. DOI=10.5120/15103-2747

@article{ 10.5120/15103-2747,
author = { Shantala Giraddi, Jagadeesh Pujari, Shraddha Giraddi },
title = { Exudates Detection with DBSCAN clustering and Back Propagation Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 86 },
number = { 19 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 16-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume86/number19/15103-2747/ },
doi = { 10.5120/15103-2747 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:04:38.727158+05:30
%A Shantala Giraddi
%A Jagadeesh Pujari
%A Shraddha Giraddi
%T Exudates Detection with DBSCAN clustering and Back Propagation Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 86
%N 19
%P 16-20
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Diabetic Retinopathy (DR) is the third biggest cause of blindness in India. Hard exudates are the primary signs of DR. In this paper the authors propose a novel hybrid mechanism for the detection of Exudates based DBSCAN clustering algorithm. Unlike other clustering algorithms, DBSCAN clustering does not require the number of clusters to be specified. Classification of regions is being done using a system based on Back propagation Neural Network. The authors assessed the performance of algorithm using one of the publicly available databases DIARETDB1. Sensitivity of 90% and a specificity of 85% are achieved using a lesion based performance evaluation criterion and an accuracy of 100% is obtained on image based performance evaluation criterion.

References
  1. C. Sinthanayothin , "Automated detection of diabetic retinopathy on digital fundus images", Diabetic Medicine, 19, pp 105-112, 2002.
  2. Akara Sopharak, Bunyarit Uyyanonvara, "Automatic exudates detection from diabetic retinopathy retinal image using fuzzy C-means and morphological methods", proceedings of the third conference on international Conference: Advances in Computer science and Technology, Phuket, Thailand, pp. 359-364, April 02-04, 2007.
  3. Akara Sopharak, "Comparative Analysis of Automatic Exudates Detection between Machine Learning and Traditional Approaches", IEJCE Transaction of INF & SYST, VOL. E92-D. NO. 11. 2009, pp 2264-2271.
  4. H. F. Jaafar, A. K. Nandi and W. Al-Nauimy, "Automated detection of exudates in retinal images using a split-and-merge algorithm," EUSIPCO 2010, Alborg, pp. 1622-1626, 2010.
  5. Maria Garcia, Clara I. Sanchez, Jesus Poza, Maria I. Lopez and Roberto Hornero," Detection of Hard exudates In Retinal Images using A Radial Basis classifier", Annals Of Biomedical Engineering, Vol. 37. No. 7. 2009. Pp 1448-1463
  6. R. Vijayamadheswaran, Dr. M. Arthanari, M. Sivakumar, "Detection Of Diabetic Retinopathy Using Radial Basis Function", International Journal Of Innovative Technology & Creative Engineering, Vol. 1 No. 1. 2011, pp 40-47.
  7. Neera Singh, Ramesh Chadra Tripathy, "Automates Early Detection Using Image Analysis Techniques", International Journal Of Computer Applications Volume 8-No. 2, 2010, pp 18-23
  8. Nathan Silberman, Krity Ahlrich, Rob Fergus and Lakshminarayanan Subramanian, "Case for Automated Detection of Diabetic Retinopathy", Association for Advancement of Artificial Intelligence, 2010.
  9. Vijayakumari,N. SuriyaNaraynan,"Diabetic Retinopathy-Early Detection Using Image Processing Techniques", International Journal On Computer Science and Engineering, Vol 2, No. 02, 2010, pp 357-361
  10. Asha Gowda karegouda, Asfiya Nasiha , M. A. Jayaram, "Exudates Detection in Retinal Images using Back propagation Neural Networks", International Journal Of Computer Applications, Volume 25-No 3, pp 25-31, 2011.
  11. Ivan Soares, Miguel Castelo-Branco, Antonio M, G. Pinnheiro ," Exudates Dynamic Detection In Retinal Fundus Images Based On The Noise Map Distribution", 19th European Signal processing Conference 2011, pp 46-50.
  12. Celebi,M. E "Mining biomedical images with density- based clustering" International conference on Information Technology; Coding and Computing, 2005, ITCC ,Vol 1 ,pp 163-168 .
  13. T. Kauppi, et. al "DIARETDB0: Evaluation database and morphology for diabetic retinopathy algorithm. Technical report, Lappeenranta University of Technology, Finland, 2006.
  14. T. Kauppi, et. al "DIARETDB1: diabetic retinopathy database and evaluation protocol," Technical report, Lappeenranta University of Technology of Kuopio, Finland, 2007.
Index Terms

Computer Science
Information Sciences

Keywords

Hard exudates DBSCAN clustering Diabetic Retinopathy Back propagation neural network

Powered by PhDFocusTM