A Coarse-to-Fine Framework for the 2021 Kidney and Kidney Tumor Segmentation Challenge

被引：21

作者：

Zhao, Zhongchen ^{[1
]}

Chen, Huai ^{[1
]}

Wang, Lisheng ^{[1
]}

机构：

[1] Shanghai Jiao Tong Univ, Inst Image Proc & Pattern Recognit, Dept Automat, Shanghai 200240, Peoples R China

来源：

KIDNEY AND KIDNEY TUMOR SEGMENTATION, KITS 2021 | 2022年 / 13168卷

关键词：

Automatic kidney segmentation; Kidney cancer; Coarse-to-fine framework;

D O I：

10.1007/978-3-030-98385-7_8

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Kidney cancer is one of the most common malignant tumors in the world. Automatic segmentation of kidney, kidney tumor, and kidney cyst is a essential tool for kidney cancer surgery. In this paper, we use a coarse-to-fine framework which is based on the nnU-Net and achieve accurate and fast segmentation of the kidney and kidney mass. The average Dice and surface Dice of segmentation predicted by our method on the test are 0.9077 and 0.8262, respectively. Our method outperformed all other teams and achieved 1st in the KITS2021 challenge.

引用

页码：53 / 58

页数：6

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