Authors
Hou, Xiaoshuai
Xie, Chunmei
Li, Fengyi
Yang, Nan

Abstract
Automated detection and segmentation of kidney tumors from 3D CT images is very useful for doctors to make diagnosis and treatment plan. In this paper, we described a multi-stage semantic segmentation pipeline for kidney and tumor segmentation from 3D CT images based on 3D U-Net architecture. The current method can achieve 0.9XX, 0.8XX average dice for kidney and tumor in the KiTS19 challenge.

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