3 papers
cs.CV2024
IMPROVE: Improving Medical Plausibility without Reliance on HumanValidation -- An Enhanced Prototype-Guided Diffusion Framework
Anurag Shandilya, Swapnil Bhat, Akshat Gautam +4
Generative models have proven to be very effective in generating synthetic medical images and find applications in downstream tasks such as enhancing rare disease datasets, long-ta…
cs.LG2024
Framework for Co-distillation Driven Federated Learning to Address Class Imbalance in Healthcare
Suraj Racha, Shubh Gupta, Humaira Firdowse +3
Federated Learning (FL) is a pioneering approach in distributed machine learning, enabling collaborative model training across multiple clients while retaining data privacy. Howeve…
eess.IV2024
PRISM: Privacy-preserving Inter-Site MRI Harmonization via Disentangled Representation Learning
Sarang Galada, Tanurima Halder, Kunal Deo +2
Multi-site MRI studies often suffer from site-specific variations arising from differences in methodology, hardware, and acquisition protocols, thereby compromising accuracy and re…