OCTAVE Dataset: Optical Coherence Tomography Annotated Volume Experiment
Version 1This is a large dataset of OCT 3D image volumes and pixel-level segmentation labels for the development of an deep learning model to autonomously detect and identify anatomic and pathological features of the retina. This project was described in the paper: “Identifying Retinal Features Using a Self‑Configuring CNN for Clinical Intervention” Daniel S. Kermany, Wesley Poon, Anaya Bawiskar, Natasha Nehra, Orhun Davarci, Glori Das, Matthew Vasquez, Shlomit Schaal, Raksha Raghunathan & Stephen
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This is a large dataset of OCT 3D image volumes and pixel-level segmentation labels for the development of an deep learning model to autonomously detect and identify anatomic and pathological features of the retina. This project was described in the paper: “Identifying Retinal Features Using a Self‑Configuring CNN for Clinical Intervention” Daniel S. Kermany, Wesley Poon, Anaya Bawiskar, Natasha Nehra, Orhun Davarci, Glori Das, Matthew Vasquez, Shlomit Schaal, Raksha Raghunathan & Stephen