Fine-tuning Stable Diffusion for Chest X-ray Generation
Multimodal models trained on large natural image-text pair datasets have exhibited astounding abilities in generating high-quality images (see: DALL-E 2, CLIP, and of course, Stable Diffusion). However, medical imaging data fundamentally differs from natural images. The language used to capture relevant details in medical data succinctly uses a different, narrow but semantically rich, domain-specific vocabulary.
Real-time Reconstructions of Visual Perception from fMRI
Recent advances in machine learning and computational neuroscience now allow neuroscientists to reconstruct visual perception from human brain activations, with the caveat that such models are run offline and require large amounts of training data to be collected from the same individual, rendering them infeasible for clinical use.