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Found 3 papers, 1 papers with code
Selective Synthetic Augmentation with HistoGAN for Improved Histopathology Image Classification
Histopathological analysis is the present gold standard for precancerous lesion diagnosis.
A Multi-attribute Controllable Generative Model for Histopathology Image Synthesis
Generative models have been applied in the medical imaging domain for various image recognition and synthesis tasks.
Synthetic Sample Selection via Reinforcement Learning
However, the quality control of synthetic images for data augmentation purposes is under-investigated, and some of the generated images are not realistic and may contain misleading features that distort data distribution when mixed with real images.
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