Summary

We are developing an open source fully-automated software program with demonstrated high accuracy that is able to detect, segment, and analyze Neovascular AMD (NVAMD) pathology seen on optical coherence tomography and compare these data to corresponding features on other imaging modalities. We anticipate that the software tools developed in this proposal will be readily adopted by clinicians, clinical study sites, and image Reading Centers to better identify NVAMD at the earliest stages, to quantify disease progression, and to measure response to therapy.

Project Details

We are developing a fully-automated software program with demonstrated high accuracy that is able to detect, segment, and analyze neovascular AMD (NVAMD) pathology seen on spectral domain optical coherence tomography (SDOCT) and compare these data to corresponding features on other imaging modalities.