Neural Network Based Approach for Detection and Classification of Diabetic Retinopathy

Authors

  • Vinod S. Wadne Department of Computer Engineering, JSPM’s ICOER, Wagholi, Pune, India
  • Ashish P. Gaigol Department of Computer Engineering, JSPM’s ICOER, Wagholi, Pune, India
  • Shubham R. Bhandari Department of Computer Engineering, JSPM’s ICOER, Wagholi, Pune, India
  • Rekha S. Kotwal Department of Information Technology, JSPM’s BSIOTR, Wagholi, Pune,India
  • Suvarna A. Wakure Department of Electronics and Telecommunication Trinity Academy of Engineering, Pune, India
  • Rupesh G. Mahajan Department of Computer Engineering, Dr. D. Y. Patil Institute of Technology, Pune

Keywords:

CNN, Retinal Image, Matrix, Diabetic, Retonopathy (DR)

Abstract

Prolonged diabetes DR can cause eye abnormalities. As the pain progresses, it can cause paralysis and blindness. Evaluation of DR using the shadow fundus is a difficult and time – consuming task because the physician must determine the visual perception of light. We propose to use CNNs to analyse DR from computer images. In our research, we use a different technique by dividing the entire image into parts and performing additional operations only on the region of interest. The planning process clearly outlines disaster recovery and helps connect clients with expert professionals. This allows customers to share their questions and get qualified members on medical topics.

 

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References

M. Mohsin Butt , Ghazanfar Latif , D.NF. Awang Iskandar , Jaafar Alghazo , Adil H. Khan , “ Multi- channel Convolutions Neural Network Based Diabetic Retinopathy

Detection from Fundus Images “ 16th International Learning & Technology Conference 2019.

Yi, S.-L.; Yang, X.-L.; Wang, T.-W., She, F.-R.: Xiong, X.; He, J.-F. Diabetic Retinopathy Diagnosis Based on RA-EfficientNet. Appl. Sci. 2021, 11, 11035. https://doi.org/10.3390/app112211035.

Gao Jinfeng, 1, 2 Sehrish Qummar, 1, 3 Zhang Junming, 1, 2, 4 Yao Ruxian, and Fiaz Gul Khan3. Ensemble Framework of Deep CNNs for Diabetic Retinopathy Detection" Hindawi Computational Intelligence and Neuroscience Volume 2020.

Kang Zhou 1;2, Zaiwang Gu2;3, Wen Liul, Weixin Luol, Jun Cheng2, Shenghua Gao1, Jiang Liu2. Multi-Cell Multi-Task Convolutional Neural Networks for Diabetic Retinopathy Grading" 978-1- 5386-3646-6/18/$31.00 ©2018 IEEE.

Sahil Chelaramani1, Manish Gupta1, Vipul Agarwall, Prashant Gupta1. Ranya Habash2 1Microsoft, 2Bascom Palmer Eye Institute. Multi- Task Knowledge Distillation for Eye Disease Prediction" 2021 IEEE Winter Conference on Applications of Computer Vision (WACV).

Ms. P. V. Amabtkar, Dr. R. S. Deshpande, ”Interpretabl Deep Learning Models: Enhancing Transparency and Trustworthiness in Explainable AI”,vol.11, 2023.

Nikhil M N1, Angel Rose A2. Diabetic Retinopathy Stage Classification using CNN" International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 05 | May 2019.

Y. Sravani Devi, S. Phani Kumar Research scholar, HOD-CSE, GITAM University Hyderabad, CSE." Y. Sravani Devi, S. Phani Kumar Research scholar, HOD-CSE, GITAM university Hyderabad, CSE" Volume 26, Issue 11, 2020.

Tariq, H.; Rashid, M.; Javed, A.; Zafar, E.; Alotaibi, S.S.; Zia. M.Y.I. Performance Analysis of Deep-Neural-Network-Based Automatic Diagnosis of Diabetic Retinopathy. Sensors 2022, 22, 205. https://doi.org/10.3390/s22010205.

A. S. Ladkat, S. S. Patankar and J. V. Kulkarni, "Modified matched filter kernel for classification of hard exudate, 2016 International Conference on Inventive Computation Technologies (ICICT), 2016, pp. 1-6, doi: 10.1109/INVENTIVE.2016.7830123.

Ana Oliveira, Yosef Ben-David, Susan Smit, Elena Popova, Milica Milić. Machine Learning for Forecasting and Predictive Modeling in Decision Science. Kuwait Journal of Machine Learning, 2(3). Retrieved from http://kuwaitjournals.com/index.php/kjml/article/view/199

Jahan, K. ., Kalyani, P. ., Sai, V. S. ., Prasad, G. ., Inthiyaz, S. ., & Ahammad, S. H. . (2023). Design and Analysis of High Speed Multiply and Accumulation Unit for Digital Signal Processing Applications. International Journal on Recent and Innovation Trends in Computing and Communication, 11(1), 95–102. https://doi.org/10.17762/ijritcc.v11i1.6055

Sherje, N.P., Agrawal, S.A., Umbarkar, A.M., Kharche, P.P., Dhabliya, D. Machinability study and optimization of CNC drilling process parameters for HSLA steel with coated and uncoated drill bit (2021)

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Published

10.11.2023

How to Cite

Wadne, V. S. ., Gaigol, A. P. ., Bhandari, S. R. ., Kotwal, R. S. ., Wakure, S. A. ., & Mahajan, R. G. . (2023). Neural Network Based Approach for Detection and Classification of Diabetic Retinopathy. International Journal of Intelligent Systems and Applications in Engineering, 12(4s), 180–186. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3762

Issue

Vol. 12 No. 4s (2024)

Section

Research Article

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