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Abstract #2476

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

Sailong Zhang1, Keith Wan-Hang Chiu1, Siu Hin Mak2, TSOUGENIS Efstratios3, and Peng Cao1
1Diagnostic Radiology, The University of Hong Kong, Hong Kong, Hong Kong, 2The University of Hong Kong, Hong Kong, Hong Kong, 3Imsight Medical Technology Company (Hong Kong), Hong Kong, Hong Kong

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.

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