Text-prompt fine-tuned Stable Diffusion can generate diverse synthetic colonoscopy polyp images, and using them as augmentation improves polyp classification balanced accuracy by up to 7.91%.
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Diverse Image Generation with Diffusion Models and Cross Class Label Learning for Polyp Classification
Text-prompt fine-tuned Stable Diffusion can generate diverse synthetic colonoscopy polyp images, and using them as augmentation improves polyp classification balanced accuracy by up to 7.91%.