Fig. 10: SLIVER-net.
From: Automated identification of clinical features from sparsely annotated 3-dimensional medical imaging
Our model operated on a 2d tiling of the OCT volume. Resnet18 served as the abstract feature extractor, and the representations for each slice were aggregated using slice integration and a 1D CNN. Finally, biomarkers were predicted using fully connected layers.
