5 citations · 6 across the 4 of their papers we have counts for
5 papers
OCT-FedSIR: Toward Trustworthy Federated Ophthalmic Learning under Annotation Noise
Sina Gholami, Abdulmoneam Ali, Tania Haghighi +8
Federated learning enables collaborative model development without centralizing patient data, but annotation reliability at participating institutions cannot always be assumed. In…
Cross-Modal Fusion of OCT and OCT angiography enface for Improved Diagnostics of Diabetic Retinopathy
Rashadul Hasan Badhon, Atalie Carina Thompson, Jennifer I. Lim +2
Diabetic retinopathy (DR) is a leading cause of vision impairment worldwide, highlighting the need for accurate and accessible screening tools. Optical Coherence Tomography (OCT) p…
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…
A Deep-learning Approach for Prognosis of Age-Related Macular Degeneration Disease using SD-OCT Imaging Biomarkers
Imon Banerjee, Luis de Sisternes, Joelle Hallak +4
We propose a hybrid sequential deep learning model to predict the risk of AMD progression in non-exudative AMD eyes at multiple timepoints, starting from short-term progression (3-…