Automated Segmentation of Right Ventricle in CMR Images based on Dense and Multi-scale U-net Network

It is essential to segment right ventricle (RV) for evaluating cardiac functional parameters of cardiac diseases in clinical diagnosis and prognosis. However, the complex structure of RV makes traditional segmentation methods not so effective in right ventricular segmentation. A new Dense and Multi-scale U-net deep learning method is proposed to segment right ventricle in cine cardiac magnetic resonance (CMR) short-axis images automatically, which shows high coincidence and small difference with manual segmentation and is promising for diagnosis and analysis of clinical cardiac diseases.