电子学报 ›› 2021, Vol. 49 ›› Issue (4): 706-715.DOI: 10.12263/DZXB.20200101
王瑞豪, 刘哲, 宋余庆
收稿日期:
2020-01-15
修回日期:
2020-06-30
出版日期:
2021-04-25
通讯作者:
作者简介:
基金资助:
WANG Rui-hao, LIU Zhe, SONG Yu-qing
Received:
2020-01-15
Revised:
2020-06-30
Online:
2021-04-25
Published:
2021-04-25
摘要: 当前基于深度学习的胰腺分割主要存在以下问题:(1)胰腺的解剖特异性导致深度网络模型容易受到复杂多变背景的干扰;(2)传统两阶段分割方法在粗分割阶段将整张CT图像作为输入,导致依赖粗分割结果得到的定位不够准确;(3)传统两阶段分割方法忽略了切片间的上下文信息,限制了定位和后续分割结果的提升.针对上述问题,本文提出了结合切片上下文信息的多阶段胰腺定位与分割方法.第一阶段利用解剖先验定位粗略缩小输入区域;第二阶段先使用所设计的DASU-Net进行粗略分割,接着利用切片上下文信息优化分割结果;第三阶段使用单张切片定位进一步减少不相关背景,并使用DASU-Net完成精细分割.实验结果表明,本文所提方法能够有效提高胰腺分割的准确率.
中图分类号:
王瑞豪, 刘哲, 宋余庆. 结合切片上下文信息的多阶段胰腺定位与分割[J]. 电子学报, 2021, 49(4): 706-715.
WANG Rui-hao, LIU Zhe, SONG Yu-qing. Multi-Stage Pancreas Localization and Segmentation Combined with Slices Context Information[J]. Acta Electronica Sinica, 2021, 49(4): 706-715.
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