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Title: :  Detection and classification of diabetic retinopathy using convolutional neural networks and fundus images
PaperId: :  9349
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 4 Issue 6 2018
DUI:    16.0415/IJARIIE-9349
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Udayan BirajdarNBN Sinhgad School of Engineering(Pune University)
Sanket GadhaveNBN Sinhgad School of Engineering (Pune University)
Shubham DadhichNBN Sinhgad School of Engineering (Pune University)
Shreyas ChikodikarNBN Sinhgad School of Engineering (Pune University)

Abstract

Computer Engineering
Diabetic Retinopathy , Convolution Neural Networks, Artificial Intelligence
There are countless number of people with diabetes around the world. Diabetic Retinopathy (DR), a major complication of diabetes, is a retinal disease that results in blindness. Early detection can prevent or delay the loss of vision due to DR. For early detection, it is essential for diabetic patients to undergo frequent retinal tests. Diagnosing DR using fundus images is a complex process and thus difficult and time consuming task requiring professional expertise to identify if the DR traits are present in eye. We propose a system that can provide immediate feedback thus effectively simplifying the process. Convolutional Neural Network (CNN) architecture based on fundus image database to accurately diagnose DR with minimum efforts on the part of patient and doctor is developed. The database contains multiple cases of retinal hemorrhage, micro-aneurism, cotton-woolspots, etc. The retinal image of the patient is fed to the system where image is processed to detect signs of DR. The network is also trained to classify various stages of DR depending on severity such as nonproliferative DR or proliferative DR. The output contains a report detailing if DR is present or not in the retinal image in question and if present, which stage it is.

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IJARIIE Udayan Birajdar, Sanket Gadhave, Shubham Dadhich, and Shreyas Chikodikar. "Detection and classification of diabetic retinopathy using convolutional neural networks and fundus images" International Journal Of Advance Research And Innovative Ideas In Education Volume 4 Issue 6 2018 Page 505-510
MLA Udayan Birajdar, Sanket Gadhave, Shubham Dadhich, and Shreyas Chikodikar. "Detection and classification of diabetic retinopathy using convolutional neural networks and fundus images." International Journal Of Advance Research And Innovative Ideas In Education 4.6(2018) : 505-510.
APA Udayan Birajdar, Sanket Gadhave, Shubham Dadhich, & Shreyas Chikodikar. (2018). Detection and classification of diabetic retinopathy using convolutional neural networks and fundus images. International Journal Of Advance Research And Innovative Ideas In Education, 4(6), 505-510.
Chicago Udayan Birajdar, Sanket Gadhave, Shubham Dadhich, and Shreyas Chikodikar. "Detection and classification of diabetic retinopathy using convolutional neural networks and fundus images." International Journal Of Advance Research And Innovative Ideas In Education 4, no. 6 (2018) : 505-510.
Oxford Udayan Birajdar, Sanket Gadhave, Shubham Dadhich, and Shreyas Chikodikar. 'Detection and classification of diabetic retinopathy using convolutional neural networks and fundus images', International Journal Of Advance Research And Innovative Ideas In Education, vol. 4, no. 6, 2018, p. 505-510. Available from IJARIIE, http://ijariie.com/AdminUploadPdf/Detection_and_classification_of_diabetic_retinopathy_using_convolutional_neural_networks_and_fundus_images_ijariie9349.pdf (Accessed : 22 October 2021).
Harvard Udayan Birajdar, Sanket Gadhave, Shubham Dadhich, and Shreyas Chikodikar. (2018) 'Detection and classification of diabetic retinopathy using convolutional neural networks and fundus images', International Journal Of Advance Research And Innovative Ideas In Education, 4(6), pp. 505-510IJARIIE [Online]. Available at: http://ijariie.com/AdminUploadPdf/Detection_and_classification_of_diabetic_retinopathy_using_convolutional_neural_networks_and_fundus_images_ijariie9349.pdf (Accessed : 22 October 2021)
IEEE Udayan Birajdar, Sanket Gadhave, Shubham Dadhich, and Shreyas Chikodikar, "Detection and classification of diabetic retinopathy using convolutional neural networks and fundus images," International Journal Of Advance Research And Innovative Ideas In Education, vol. 4, no. 6, pp. 505-510, Nov-Dec 2018. [Online]. Available: http://ijariie.com/AdminUploadPdf/Detection_and_classification_of_diabetic_retinopathy_using_convolutional_neural_networks_and_fundus_images_ijariie9349.pdf [Accessed : 22 October 2021].
Turabian Udayan Birajdar, Sanket Gadhave, Shubham Dadhich, and Shreyas Chikodikar. "Detection and classification of diabetic retinopathy using convolutional neural networks and fundus images." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 4 number 6 (22 October 2021).
Vancouver Udayan Birajdar, Sanket Gadhave, Shubham Dadhich, and Shreyas Chikodikar. Detection and classification of diabetic retinopathy using convolutional neural networks and fundus images. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2018 [Cited : 22 October 2021]; 4(6) : 505-510. Available from: http://ijariie.com/AdminUploadPdf/Detection_and_classification_of_diabetic_retinopathy_using_convolutional_neural_networks_and_fundus_images_ijariie9349.pdf
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