SCCNN: A Diagnosis Method for Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma Based on Siamese Cross Contrast Neural Network

SCCNN: A Diagnosis Method for Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma Based on Siamese Cross Contrast Neural Network

This paper proposes a novel siamese cross contrast neural network (SCCNN) to classify the hepatocellular carcinoma (HCC) and the intrahepatic cholangiocarcinoma (ICC) on computed tomography (CT) images. This method is inspired from cross contrast neural networks (CCNN) which is based on tailored CNN...

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Bibliographic Details
Main Authors: Qiyuan Wang, Zhongmin Wang, Yu Sun, Xin Zhang, Weifeng Li, Yun Ge, Xiaolin Huang, Yun Liu, Ying Chen
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Siamese networks
multiple loss
cross contrast neural networks
hepatocellular carcinoma
intrahepatic cholangiocarcinoma
Online Access:https://ieeexplore.ieee.org/document/9086453/

Internet

https://ieeexplore.ieee.org/document/9086453/

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