A Novel Coarse-to-Fine Segmentation Method for Pancreatic Cancer

被引：0

作者：

Wang Zhisheng ^{[1
]}

Li Qing ^{[1
]}

Ding Xuehai ^{[1
]}

机构：

[1] Shanghai Univ, Shanghai 201900, Peoples R China

来源：

2020 5TH INTERNATIONAL CONFERENCE ON SMART GRID AND ELECTRICAL AUTOMATION (ICSGEA 2020) | 2020年

关键词：

Pancreatic Cancer Segmentation; Background Interference; Coarse-to-Fine; Dice Similarity Coefficient; GRADIENT;

D O I：

10.1109/ICSGEA51094.2020.00045

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Pancreatic cancer is one of the most deadly cancers, with a 5-year survival rate of only 8%, but early diagnosis can increase the survival rate to about 20 /0. Therefore, by examining abdominal CT scans, early and accurate diagnosis of pancreatic tumors is critical to treatment decisions. In CT images, pancreatic cancer faces imbalanced classification, background interference, and non-rigid geometric features, making it difficult for even experienced radiologists to diagnose. Therefore, we propose a novel method to detect pancreatic cancer more accurately. In order to make the positioning more accurate, we use a rough segmentation network to get a rough positioning, and then get a more accurate segmentation effect based on this positioning. We trained and tested on a public data set containing 281 cases, and the dsc coefficient reached 63.4 +/- 23.67%. This experiment proves that our proposed new method is effective and shows potential clinical impact.

引用

页码：176 / 181

页数：6

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