Model for detecting retina damage from Optical Coherence Tomography (OCT) Images, using Transfer Learning on VGG16 CNN Model.
Retinal Optical Coherence Tomography (OCT) is an imaging technique used to capture high-resolution cross sections of the retinas of living patients. Approximately 30 million OCT scans are performed each year, and the analysis and interpretation of these images takes up a significant amount of time (Swanson and Fujimoto, 2017).
Data is avalaible here : https://data.mendeley.com/datasets/rscbjbr9sj/2
A VGG16 CNN architecture is used for calssification pretrained on the 'ImageNet' dataset. The full code is available here https://colab.research.google.com/drive/1UzymPZ7DOG9JO2nOEA4IndMaed1kzQyK?usp=sharing