Liver lesion segmentation in CT images with MK-FCN

Abstract

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.