2 citations · 3 across the 4 of their papers we have counts for
4 papers
Envisioning MedCLIP: A Deep Dive into Explainability for Medical Vision-Language Models
Anees Ur Rehman Hashmi, Dwarikanath Mahapatra, Mohammad Yaqub
Explaining Deep Learning models is becoming increasingly important in the face of daily emerging multimodal models, particularly in safety-critical domains like medical imaging. Ho…
Prompt-driven Latent Domain Generalization for Medical Image Classification
Siyuan Yan, Chi Liu, Zhen Yu +7
Deep learning models for medical image analysis easily suffer from distribution shifts caused by dataset artifacts bias, camera variations, differences in the imaging station, etc.…
Domain Generalization by Learning from Privileged Medical Imaging Information
Steven Korevaar, Ruwan Tennakoon, Ricky O'Brien +2
Learning the ability to generalize knowledge between similar contexts is particularly important in medical imaging as data distributions can shift substantially from one hospital t…
AMAE: Adaptation of Pre-Trained Masked Autoencoder for Dual-Distribution Anomaly Detection in Chest X-Rays
Behzad Bozorgtabar, Dwarikanath Mahapatra, Jean-Philippe Thiran
Unsupervised anomaly detection in medical images such as chest radiographs is stepping into the spotlight as it mitigates the scarcity of the labor-intensive and costly expert anno…