MSI-UNet: A Flexible UNet-Based Multi-Scale Interactive Framework for 3D Gastric Tumor Segmentation on CT Scans-Reference-Cited by-同舟云学术

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MSI-UNet: A Flexible UNet-Based Multi-Scale Interactive Framework for 3D Gastric Tumor Segmentation on CT Scans

Published:2024-05-27 Issue: Volume: Page:1-5
ISSN:
Container-title:2024 IEEE International Symposium on Biomedical Imaging (ISBI)
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Author:

Chen Heyun¹,Chen Zifan¹,Zhao Jie²,Li Haoshen¹,Li Jiazheng³,Liu Yiting³,Yuan Mingze¹,Bao Peng¹,Nan Xinyu¹,Dong Bin⁴,Tang Lei³,Zhang Li¹

Affiliation:

1. Center for Data Science, Peking University,China

2. Peking University,National Engineering Laboratory for Big Data Analysis and Applications,China

3. Peking University Cancer Hospital&Institute,China

4. Peking University,Beijing International Center for Mathematical Research,China

Funder

National Natural Science Foundation of China

Peking University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10635099/10635102/10635129.pdf?arnumber=10635129

Reference17 articles.

1. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

2. CT and PET/CT Scans in Gastric Cancer Diagnosis

3. Current treatment and recent progress in gastric cancer

4. Deep Retinal Image Segmentation With Regularization Under Geometric Priors

5. U-Net: Convolutional Networks for Biomedical Image Segmentation

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