SynthDL Dataset and Code
Abstract
Manual orthopedic X-ray diagnosis suffers from a combination of human error and time cost. However, due to privacy concerns, existing datasets are small and contain adversarial data which hinder the development of computer aided diagnosis tools. In this study, we evaluate the efficacy of latent diffusion models for the generation of synthetic elbow radiographs. We present a mask-based fine-tuning methodology for the Stable Diffusion 1.0 XL and Flux.1 Fill Dev image generation models.
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