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Found 2 papers, 1 papers with code
RadRotator: 3D Rotation of Radiographs with Diffusion Models
This transformation makes the diffusion model agnostic to any distribution variations of the input data pixel intensity, enabling the reliable training of a DL model on input DRRs and applying the exact same model to conventional radiographs (or DRRs) during inference.
Synthetically Enhanced: Unveiling Synthetic Data's Potential in Medical Imaging Research
This study examines the impact of synthetic data supplementation, using diffusion models, on the performance of deep learning (DL) classifiers for CXR analysis.
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