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Pancreatic Tumor Segmentation Based on 3D U-Net with Densely Connected Atrous Spatial Pyramid Module and Attention Module

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成果类型:
期刊论文、会议论文
作者:
Deng, Jiakun;Mou, Yi
通讯作者:
Mou, Y
作者机构:
[Mou, Yi; Deng, Jiakun] Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan, Peoples R China.
通讯机构:
[Mou, Y ] W
Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan, Peoples R China.
语种:
英文
关键词:
pancreatic tumor;image segmentation;Densely Connected Atrous Spatial Pyramid;Attention Module
期刊:
PROCEEDINGS OF 2023 4TH INTERNATIONAL SYMPOSIUM ON ARTIFICIAL INTELLIGENCE FOR MEDICINE SCIENCE, ISAIMS 2023
年:
2023
页码:
51–58
会议名称:
4th International Symposium on Artificial Intelligence for Medicine Science (ISAIMS)
会议论文集名称:
ISAIMS '23: Proceedings of the 2023 4th International Symposium on Artificial Intelligence for Medicine Science
会议时间:
OCT 20-22, 2023
会议地点:
Chengdu, PEOPLES R CHINA
会议主办单位:
[Deng, Jiakun;Mou, Yi] Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan, Peoples R China.
出版地:
1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES
出版者:
ASSOC COMPUTING MACHINERY
ISBN:
979-8-4007-0813-8
机构署名:
本校为第一且通讯机构
院系归属:
电气与电子工程学院
摘要:
The segmentation of CT images of pancreatic tumors is of great significance for the diagnosis and treatment of pancreatic tumors. Due to the small size and irregular shape of pancreatic tumors, precise segmentation of pancreatic tumor CT images using neural networks remains a challenge in machine learning. At present, the dice coefficient, MIoU coefficient, and Precision coefficient of neural network for pancreatic tumor CT image segmentation are only 50%, 30%, and 50% at most, respectively. There is a lot of room to improve the segmentation effect. This paper proposes a CT image segmentation ...

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