Transfer Learning based Classification of Diabetic Retinopathy on the Kaggle EyePACS dataset

Research output: Contribution to conferencePaperpeer-review

Abstract

Severe stages of diabetes can eventually lead to an eye condition
called diabetic retinopathy. It is one of the leading causes of temporary visual disability and permanent blindness. There is no cure for this disease other than a proper treatment in the early stages. Five stages of diabetic retinopathy are discussed in this paper that need to be detected followed by a proper treatment. Transfer learning is used to detect the grades of diabetic retinopathy in eye fundus images, without training from scratch. The Kaggle EyePACS dataset is one of the largest datasets
available publicly for experimentation. In our work, an extensive study on the Kaggle EyePACS dataset is carried out using pre-trained models ResNet50 and DenseNet121. The Aptos dataset is also used in comparison with this dataset to examine the performance of the pre-trained models. Different experiments are performed to analyze the images from the different classes in the Kaggle EyePACS dataset. This dataset has significant challenges including image noise, imbalanced classes, and fault annotations. Our work highlights potential problems within the dataset
and the conflicts between the classes. A clustering technique is used to get informative images from the normal class to improve the model’s accuracy to 70%.
Original languageEnglish
Publication statusAccepted/In press - 15 Nov 2022
EventThe 3rd International Conference on Medical Imaging and Computer-Aided Diagnosis - University of Leicester, United Kingdom, Leicester, United Kingdom
Duration: 20 Nov 202221 Nov 2022
Conference number: 3
https://www.micad.org/

Conference

ConferenceThe 3rd International Conference on Medical Imaging and Computer-Aided Diagnosis
Country/TerritoryUnited Kingdom
CityLeicester
Period20/11/2221/11/22
Internet address

Fingerprint

Dive into the research topics of 'Transfer Learning based Classification of Diabetic Retinopathy on the Kaggle EyePACS dataset'. Together they form a unique fingerprint.

Cite this