Liver Lesion Segmentation in CT Images with MK-FCN

摘要：

　　This paper presented an approach used Fully Convolutional Networks(FCN)to segment liver tumor in Computed Tomography(CT)images.In addition,using different characteristics of scan quality and tumor conspicuity among portal venous phase,arterial phase and equilibrium phase,we proposed an automatic liver tumor segmentation with Multiple Kernel Fully Convolutional Networks(MK-FCN).MK-FCN can segment liver tumor from multi-phase contrast-enhanced CT images by using different characteristics of scan quality and tumor conspicuity among different phases.Experiments proved the effectiveness of this method in the liver tumor segmentation.

关键词： Multiple Kernel liver tumor segmentation multi-phase contrast-enhanced

作者: Changjian Sun Shuxu Guo Huimao Zhang Jing Li Shuzhi Ma Xueyan Li

作者单位: College of Electronic Science and Engineering,Jilin University Department of Radiology,The First Hospital of Jilin University Changchun,China

会议类型: 国际会议

会议名称: 2017 IEEE 2nd Advanced Information Technology,Electronic and Automation Control Conference(IAEAC 2017)(2017 IEEE 第2届先进信息技术、电子与自动化控制国际会议)

会议地点: 重庆

会议语种:英文

页码: 1794-1798

在线出版日期: 2017-03-25（万方平台首次上网日期，不代表论文的发表时间）