192 citations · 729 across the 35 of their papers we have counts for
43 papers
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…
DermSynth3D: Synthesis of in-the-wild Annotated Dermatology Images
Ashish Sinha, Jeremy Kawahara, Arezou Pakzad +6
In recent years, deep learning (DL) has shown great potential in the field of dermatological image analysis. However, existing datasets in this domain have significant limitations,…
MaskTune: Mitigating Spurious Correlations by Forcing to Explore
Saeid Asgari Taghanaki, Aliasghar Khani, Fereshte Khani +4
A fundamental challenge of over-parameterized deep learning models is learning meaningful data representations that yield good performance on a downstream task without over-fitting…
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…