Automatic Detection and Segmentation of Liver Tumors in Multi- phase CT Images by Phase Attention Mask R-CNN

In computer-aided diagnosis of liver tumors, tumor detection and segmentation are essential pretreatment steps. In this study, we proposed a phase attention mask R-CNN based method for simultaneous detection and segmentation of liver tumors in multi-phase CT images. Each feature of the triple phase image is selectively extracted by the attention network for each scale. The segmentation accuracy (Dice value) is about 0.60 ~ 0.66 for single-phase CT images, and the accuracy can be improved to about 0.77 by the proposed method using attention network with multi-phase CT images.