192 citations · 729 across the 35 of their papers we have counts for
27 papers · 1 filter
AViT: Adapting Vision Transformers for Small Skin Lesion Segmentation Datasets
Siyi Du, Nourhan Bayasi, Ghassan Hamarneh +1
Skin lesion segmentation (SLS) plays an important role in skin lesion analysis. Vision transformers (ViTs) are considered an auspicious solution for SLS, but they require more trai…
MDViT: Multi-domain Vision Transformer for Small Medical Image Segmentation Datasets
Siyi Du, Nourhan Bayasi, Ghassan Hamarneh +1
Despite its clinical utility, medical image segmentation (MIS) remains a daunting task due to images' inherent complexity and variability. Vision transformers (ViTs) have recently…
CIRCLe: Color Invariant Representation Learning for Unbiased Classification of Skin Lesions
Arezou Pakzad, Kumar Abhishek, Ghassan Hamarneh
While deep learning based approaches have demonstrated expert-level performance in dermatological diagnosis tasks, they have also been shown to exhibit biases toward certain demogr…
FairDisCo: Fairer AI in Dermatology via Disentanglement Contrastive Learning
Siyi Du, Ben Hers, Nourhan Bayasi +2
Deep learning models have achieved great success in automating skin lesion diagnosis. However, the ethnic disparity in these models' predictions, where lesions on darker skin types…
Deep Multimodal Guidance for Medical Image Classification
Mayur Mallya, Ghassan Hamarneh
Medical imaging is a cornerstone of therapy and diagnosis in modern medicine. However, the choice of imaging modality for a particular theranostic task typically involves trade-off…
One Map Does Not Fit All: Evaluating Saliency Map Explanation on Multi-Modal Medical Images
Weina Jin, Xiaoxiao Li, Ghassan Hamarneh
Being able to explain the prediction to clinical end-users is a necessity to leverage the power of AI models for clinical decision support. For medical images, saliency maps are th…