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

Liver segmentation in CT images using three dimensional to two dimensional fully convolutional network