Unsupervised domain adaptation in biomedical images segmentation with guided diffusion generative prior

Puntos clave

• The aim is to enhance segmentation of biomedical images using unsupervised domain adaptation combined with guided diffusion generative priors.
• Utilized unsupervised domain adaptation techniques for image segmentation
• Implemented guided diffusion methods to improve generative modeling
• Evaluated segmentation performance on various biomedical datasets
• Achieved improved segmentation accuracy compared to traditional methods
• Demonstrated the ability to generalize across different biomedical image domains
• Showcased significant reductions in segmentation errors