Automatic detection of age-related macular
degeneration (AMD) from optical coherence tomography
(OCT) images is often performed using the retinal layers
only and choroid is excluded from the analysis. This is
because symptoms of AMD manifest in the choroid only
in the later stages and clinical literature is divided over
the role of the choroid in detecting earlier stages of AMD.
However, more recent clinical research suggests that choroid
is affected at a much earlier stage. In the proposed work, we
experimentally verify the effect of including the choroid in
detecting AMD from OCT images at an intermediate stage.
We propose a deep learning framework for AMD detection
and compare its accuracies with and without including the
choroid. Results suggest that including the choroid improves
the AMD detection accuracy. In addition, the proposed method
achieves an accuracy of 96.78% which is comparable to the