142 citations · 272 across the 11 of their papers we have counts for
12 papers
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…
FedEDAuth -- Federated Embedding Distribution Authentication for Counterfeit IC Detection
Naseeruddin Lodge, Dhruva Aklekar, Vineet Chadalavada +4
The widespread of counterfeit integrated circuits (ICs) poses severe risks to the security, reliability, and trustworthiness of modern electronic systems. Federated learning (FL) o…
Anatomy-Aware Unsupervised Detection and Localization of Retinal Abnormalities in Optical Coherence Tomography
Tania Haghighi, Sina Gholami, Hamed Tabkhi +1
Reliable automated analysis of Optical Coherence Tomography (OCT) imaging is crucial for diagnosing retinal disorders but faces a critical barrier: the need for expensive, labor-in…
FedSIR: Spectral Client Identification and Relabeling for Federated Learning with Noisy Labels
Sina Gholami, Abdulmoneam Ali, Tania Haghighi +2
Federated learning (FL) enables collaborative model training without sharing raw data; however, the presence of noisy labels across distributed clients can severely degrade the lea…
Domain Adaptation of Large Language Models for Polymer-Composite Additive Manufacturing Using Retrieval-Augmented Generation and Fine-Tuning
Saiful Islam Sagor, Tania Haghighi, Minhaj Nur Alam +1
General-purpose large language models (LLMs) often struggle to generate reliable responses in specialized engineering domains due to limited domain grounding and insufficient expos…
Multi-OCT-SelfNet: Integrating Self-Supervised Learning with Multi-Source Data Fusion for Enhanced Multi-Class Retinal Disease Classification
Fatema-E- Jannat, Sina Gholami, Jennifer I. Lim +3
In the medical domain, acquiring large datasets poses significant challenges due to privacy concerns. Nonetheless, the development of a robust deep-learning model for retinal disea…
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…
OCT-SelfNet: A Self-Supervised Framework with Multi-Modal Datasets for Generalized and Robust Retinal Disease Detection
Fatema-E Jannat, Sina Gholami, Minhaj Nur Alam +1
Despite the revolutionary impact of AI and the development of locally trained algorithms, achieving widespread generalized learning from multi-modal data in medical AI remains a si…
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…
AV-Net: Deep learning for fully automated artery-vein classification in optical coherence tomography angiography
Minhaj Alam, David Le, Taeyoon Son +2
This study is to demonstrate deep learning for automated artery-vein (AV) classification in optical coherence tomography angiography (OCTA). The AV-Net, a fully convolutional netwo…
Transfer Learning for Automated OCTA Detection of Diabetic Retinopathy
David Le, Minhaj Alam, Cham Yao +4
Purpose: To test the feasibility of using deep learning for optical coherence tomography angiography (OCTA) detection of diabetic retinopathy (DR). Methods: A deep learning convolu…
Supervised machine learning based multi-task artificial intelligence classification of retinopathies
Minhaj Alam, David Le, Jennifer I. Lim +2
Artificial intelligence (AI) classification holds promise as a novel and affordable screening tool for clinical management of ocular diseases. Rural and underserved areas, which su…