MediSinGAN
MediSinGAN
The aim is to use an unconditional generative model, SinGAN, to augment medical image datasets using a single natural image.
Current Progress
- Implemented SinGAN architecture in JAX for the generation of realistic synthetic medical imaging data using a single training image and achieved a 20% reduction in training time
- Evaluated the model applicability in MRI cross-modality image-to-image translation, Synthetic brain tumor generation, and Medical image segmentation (Histopathology)