GANs in Medical Image Synthesis, Translation, and Augmentation - Jason Jeong

This course covers the applications of Generative Adversarial Networks (GANs) in medical image synthesis, translation, and augmentation. The learning outcomes include understanding the use of GANs in medical imaging tasks such as classification and segmentation, as well as generating synthetic medical images. The course teaches skills like working with GAN architecture, medical GANs, classification methods, data augmentation techniques, and addressing data imbalance issues. The teaching method involves a presentation followed by interactive discussions and Q&A sessions. The intended audience includes individuals interested in AI applications in the medical field, particularly in medical imaging and data analysis.