Development of a deep learning algorithm for detection of liver cancers on Magnetic Resonance Imaging

Abstract

Early detection of liver cancer is crucial for improving patient management outcome. However, liver lesions can be differencaited to be identified. In recent years, the fully convolution neural network (FCNN) has shown to be able to achieve commensurate and comparable performance of detecting various pathology on medical imaging. The goal of this study is to show the possibility of applying FCNN deep learning for training the hepatic lesion detection on dynamic contrast-enhanced Magnetic Resonance Imaging.