An Image Processing Algorithm To Detect Exudates In Fundus Images

Authors

  • Anand M ECE Dept, East West Institute of Technology, Bengaluru, India
  • Meenakshi ECE Dept, East West Institute of Technology, Bengaluru, India
  • Nandini Rao M ECE Dept, East West Institute of Technology, Bengaluru, India
  • Varsha H N ECE Dept, East West Institute of Technology, Bengaluru, India
  • Yashaswini H ECE Dept, East West Institute of Technology, Bengaluru, India

DOI:

https://doi.org/10.5281/zenodo.6969918

Keywords:

Diabetic Retinopathy, Exudates, Fundus images

Abstract

Diabetic Retinopathy is often noticed in individuals suffering from diabetes. The major characteristic of this disease is the presence of exudates in the retinal area. These exudates can be scanned using fundus imaging. The aim of the project is to develop an algorithm that can identify exudates in fundus images, and based on the area, prescribe medication using the concept of content-based image retrieval. The algorithm will be developed on MATLAB and also be downloaded on a Spartan 3e FPGA.

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References

P.R. Asha and S. karpagavalli,” diabetic retinal exudates detection using machine learning techniques,”2015vinternational conference on advanced computing and communication systems (ICACCS-2015), Jan 05-07, 2015, Coimbatore INDIA.

Ravitej Singh Rakhi, Ashish Isaac, Malay Kishore Dutta amity university, Noida, India Carlos M. Travieso signals IDeTIC university of las palmas de gran Canaria,” Automated classification of exudates from digital fundus images”2017 IEEE.

Yunpu Wu, Weidong Jin, Zhenzhen chai,” Automatic Detection and Evaluation of Hard Exudates Based on Deep Bayesian Learning” Proceedings of the 37th Chinese Control Conference July 25-27,2018, Wuhan, China.

Vasanthi Satyananda, K V Narayanaswamy, Karibasappa”4. Exudate Extraction from Fundus Images”,2018. @2019 IEEE.

Avula Benzamin, Chandan Chakraborty.: Detection of Hard Exudates in Retinal Fundus Images Using Deep Learning”2018, 2nd International Conference on Imaging.

Aishwarya. Dixit “Hard exudate detection using Linear Brightness method”,2019 4th International Conference on Recent Trends on Electronics & Technology (RTEICT-2019), MAY 17th & 18th 2019.

Dulanji Lokuarachchi, Kasun Gunaratna, Lahiru Muthumal “Automated Detection of Exudates in Retinal Images”.2019 IEEE 15th international colloquium on signal processing & its applications (CSPA 2019),8-9 March 2019, Penang, Malaysia.

Vasanthi Satyananda, K V Narayanaswamy, karibasappa,” Hard exudate extraction from fundus images using watershed transform” sept 5, 2019.Indonesian Journal of electrical engineering and informatics (IJEEI)vol.7, no.3, Sep 2019, pp.449~462.

Dhan Shree thulkar, Rohin Daruwalla “detection of exudate for diabetic macular Edema classification”, 2019,2019 5th international conference on science and technology (ICST), Yogyakarta Indonesia.

Yangshuo zong, Jinling Chen,” U-net base method for automatic hard exudate segmentation in fundus images using inception module and residual connection” in 2020.

Pradip dhal “A novel approach for blood vessel segmentation with exudate detection diabetic retinopathy “2020, international conference on artificial intelligence and signal processing (AISP).

Mohammed Shafeeq Ahmed and Dr.B. Indira, “Morphological technique for detection of microaneurysms from RGB fundus image”, ID: j-16-11-160, to be published in the journal of electrical engineering and technology, Korea,2017.

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Published

2022-08-05

How to Cite

[1]
A. M, Meenakshi, N. Rao M, V. H N, and Y. H, “An Image Processing Algorithm To Detect Exudates In Fundus Images”, pices, vol. 6, no. 4, pp. 19-22, Aug. 2022.

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