age-related macular degeneration
We present ReSenseNet, a 3D to 2D deep neural network that is able to predict microperimetry maps from OCT images.
We posed a multiclass segmentation task as a single multitask model with binary segmentation targets. Our results indicate that this approach might be useful to deal with "sandwiched" structures.
We propose a deep learning methodology to predict retinal sensitivity from OCT volumes.
We used epistemic uncertainty estimates to discover potential abnormalities in diseased OCT scans. The uncertainty maps are obtained by a Bayesian U-Net trained on healthy OCT scans with weak labels of the retinal layers.