  The need for CT scan analysis is growing for pre-diagnosis and therapy of
abdominal organs. Automatic organ segmentation of abdominal CT scan can help
radiologists analyze the scans faster and segment organ images with fewer
errors. However, existing methods are not efficient enough to perform the
segmentation process for victims of accidents and emergencies situations. In
this paper we propose an efficient liver segmentation with our 3D to 2D fully
connected network (3D-2D-FCN). The segmented mask is enhanced by means of
conditional random field on the organ's border. Consequently, we segment a
target liver in less than a minute with Dice score of 93.52.
