Automatic segmentation of liver tumors from multiphase contrast-enhanced CT images based on FCNs
作者：
Highlights：
• The multi-channel fully convolutional networks is designed.
• We segment liver tumors from multiphase contrast-enhanced CT images.
• We train one network for each phase of CT images and fuse their high-layer features together.
• This method can make full use of the characteristics of different enhancement phases of CT images.
• The results showed our model provided greater accuracy and robustness than previous methods.
摘要
•The multi-channel fully convolutional networks is designed.•We segment liver tumors from multiphase contrast-enhanced CT images.•We train one network for each phase of CT images and fuse their high-layer features together.•This method can make full use of the characteristics of different enhancement phases of CT images.•The results showed our model provided greater accuracy and robustness than previous methods.
论文关键词：Fully convolutional networks,Multi-channel,Feature fusion
论文评审过程：Received 30 December 2016, Revised 28 February 2017, Accepted 10 March 2017, Available online 27 March 2017, Version of Record 17 November 2017.
论文官网地址：https://doi.org/10.1016/j.artmed.2017.03.008
