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Introducing SDICE: An Index for Assessing Diversity of Synthetic Medical Datasets
Mohammed Talha Alam, Raza Imam, Mohammad Areeb Qazi +2
Advancements in generative modeling are pushing the state-of-the-art in synthetic medical image generation. These synthetic images can serve as an effective data augmentation metho…
PromptSmooth: Certifying Robustness of Medical Vision-Language Models via Prompt Learning
Noor Hussein, Fahad Shamshad, Muzammal Naseer +1
Medical vision-language models (Med-VLMs) trained on large datasets of medical image-text pairs and later fine-tuned for specific tasks have emerged as a mainstream paradigm in med…
Makeup-Guided Facial Privacy Protection via Untrained Neural Network Priors
Fahad Shamshad, Muzammal Naseer, Karthik Nandakumar
Deep learning-based face recognition (FR) systems pose significant privacy risks by tracking users without their consent. While adversarial attacks can protect privacy, they often…
BAPLe: Backdoor Attacks on Medical Foundational Models using Prompt Learning
Asif Hanif, Fahad Shamshad, Muhammad Awais +5
Medical foundation models are gaining prominence in the medical community for their ability to derive general representations from extensive collections of medical image-text pairs…
STEREO: A Two-Stage Framework for Adversarially Robust Concept Erasing from Text-to-Image Diffusion Models
Koushik Srivatsan, Fahad Shamshad, Muzammal Naseer +2
The rapid proliferation of large-scale text-to-image diffusion (T2ID) models has raised serious concerns about their potential misuse in generating harmful content. Although numero…
A Federated Learning-Friendly Approach for Parameter-Efficient Fine-Tuning of SAM in 3D Segmentation
Mothilal Asokan, Joseph Geo Benjamin, Mohammad Yaqub +1
Adapting foundation models for medical image analysis requires finetuning them on a considerable amount of data because of extreme distribution shifts between natural (source) data…