Semi-Supervised Deep Learning for Red Blood Cell Morphological Classification with Applications to Sickle Cell Disease and Hyposplenism

In this project we propose to develop a robust fully-automated real-time Red blood cells (RBC) classification method with applications to sickle cell disease (SCD) and hyposplenism (impaired spleen function), based on semi-supervised deep learning approach using generative adversarial network (GAN).