Name
Title | ||
|---|---|---|
Eye Disease Prediction from Optical Coherence Tomography Images with Transfer Learning. |
Abstract | ||
|---|---|---|
Optical Coherence Tomography (OCT) of the human eye are used by optometrists to analyze and detect various age-related eye abnormalities like Choroidal Neovascularization, Drusen (CNV), Diabetic Macular Odeama (DME), Drusen. Detecting these diseases are quite challenging and requires hours of analysis by experts, as their symptoms are somewhat similar. We have used transfer learning with VGG16 and Inception V3 models which are state of the art CNN models. Our solution enables us to predict the disease by analyzing the image through a convolutional neural network (CNN) trained using transfer learning. Proposed approach achieves a commendable accuracy of 94% on the testing data and 99.94% on training dataset with just 4000 units of data, whereas to the best of our knowledge other researchers have achieved similar accuracies using a substantially larger (almost 10 times) dataset. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/978-3-030-20257-6_9 | Communications in Computer and Information Science |
Keywords | Field | DocType |
Deep learning,Transfer learning,Convolutional Neural Networks,Artificial intelligence,Bioinformatics,Age-related macular degeneration,Choroidal Neovascularization,Pneumonia,Diabetic Retinopathy,Diabetic Macular Edema,Optical Coherence Tomography | Human eye,Eye disease,Optical coherence tomography,Choroidal neovascularization,Pattern recognition,Convolutional neural network,Computer science,Transfer of learning,Drusen,Artificial intelligence,Deep learning | Conference |
Volume | ISSN | Citations |
1000 | 1865-0929 | 1 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arka Bhowmik | 1 | 1 | 0.34 |
| Sanjay Kumar | 2 | 9 | 7.60 |
| Neeraj Bhat | 3 | 1 | 0.34 |