基于U-Net的特征交互分割方法

doi:10.16451/j.cnki.issn1003-6059.202111009

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Abstract

To address the problems of mis-segmentation and missing segmentation of small targets in liver segmentation, a U-Net based feature interaction segmentation method is proposed using ResNet34 as the backbone network. To achieve non-local interactions between different scales, a transformer-based feature interaction pyramid module is designed as the bridge of the network to obtain feature maps with richer contextual information. A multi-scale attention mechanism is designed to replace the jumping connection in U-Net, considering the small targets in the image and sufficiently acquiring the contextual information of the target layer. Experiments on the public dataset LiTS and the dataset consisting of 3Dircadb and CHAOS demonstrate that the proposed method achieves good segmentation results.

Key words： Liver Segmentation Transformer Attention Mechanism Feature Interaction

Received: 15 June 2021

ZTFLH:

TP 391.41

Fund:

Science and Technology Key Project of Henan Province(No.212102310084), Key Scientific Research Projects of Colleges and Universities in Henan Province(No.22A520027), Open Project of Jiangsu Provincial Key Laboratory for Computer Information Processing Technology of Soochow University(No.KJS2048)

Corresponding Authors: WU Xiaosheng, master, associate professor. Her research interests include image processing and pattern recognition.

About author:: SUN Junding, Ph.D., professor. His research interests include image processing and pattern recognition.
HUI Zhenkun, master student. His research interests include medical image segmentation.
TANG Chaosheng, Ph.D., lecturer. His research interests include medical image processing.

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	SUN Junding
	HUI Zhenkun
	TANG Chaosheng
	WU Xiaosheng

Cite this article:

SUN Junding,HUI Zhenkun,TANG Chaosheng等. U-Net Based Feature Interaction Segmentation Method[J]. , 2021, 34(11): 1058-1068.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202111009 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2021/V34/I11/1058

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