1 citations · 2 across the 2 of their papers we have counts for
3 papers
Quantitative Characterization of Retinal Features in Translated OCTA
Rashadul Hasan Badhon, Atalie Carina Thompson, Jennifer I. Lim +2
Purpose: This study explores the feasibility of using generative machine learning (ML) to translate Optical Coherence Tomography (OCT) images into Optical Coherence Tomography Angi…
Contrastive learning-based pretraining improves representation and transferability of diabetic retinopathy classification models
Minhaj Nur Alam, Rikiya Yamashita, Vignav Ramesh +6
Self supervised contrastive learning based pretraining allows development of robust and generalized deep learning models with small, labeled datasets, reducing the burden of label…
Quantitative optical coherence tomography reveals rod photoreceptor degeneration in early diabetic retinopathy
David Le, Taeyoon Son, Jennifer I. Lim +1
Purpose: This study is to test the feasibility of optical coherence tomography (OCT) detection of photoreceptor abnormality and to verify the photoreceptor abnormality is rod predo…