  Automated segmentation of kidney and tumor from 3D CT scans is necessary for
the diagnosis, monitoring, and treatment planning of the disease. In this
paper, we describe a two-stage framework for kidney and tumor segmentation
based on 3D fully convolutional network (FCN). The first stage preliminarily
locate the kidney and cut off the irrelevant background to reduce class
imbalance and computation cost. Then the second stage precisely segment the
kidney and tumor on the cropped patch. The proposed method ranks the 4th place
out of 105 competitive teams in MICCAI 2019 KiTS Challenge with a Composite
Dice of 90.24%.
