Synthesizing Contrast-enhanced Computed Tomography Images with an Improved Conditional Generative Adversarial Network-Reference-Cited by-同舟云学术

Synthesizing Contrast-enhanced Computed Tomography Images with an Improved Conditional Generative Adversarial Network

Published:2022-07-11 Issue: Volume: Page:
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Container-title:2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Yang Yulin¹,Iwamoto Yutaro¹,Chen Yen-Wei¹,Xu Caie²,Chen Qingqing³,Hu Hongjie³,Han Xian-Hua⁴,Tong Ruofeng⁵,Lin Lanfen⁵

Affiliation:

1. College of Information Science and Engineering, Ritsumeikan University,Shiga,Japan

2. School of Information and Electronic Engineering, Zhejiang University of Science and Technology,HangZhou,China

3. School of Medicine, Sir Run Run Shaw Hospital, Zhejiang University,Department of Radiology,Hangzhou,China

4. Artificial Intelligence Research Center, Yamaguchi University,Japan

5. Research Center for Healthcare Data Science, Zhejiang Lab,Hangzhou,China

Funder

Japanese Ministry for Education, Science, Culture and Sports (MEXT)

Natural Science Foundation of Zhejiang Province

Major Scientific Research Project of Zhejiang Lab

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9870821/9870822/09871672.pdf?arnumber=9871672

Reference18 articles.

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2. Pyramid scene parsing network;hengshuang;Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,0

3. A simple pooling-based design for real-time salient object detection;jiang-jiang;Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition,0

4. Image-to-image translation with conditional adversarial networks;phillip;Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition,0

5. Improved training of wasserstein gans;ishaan;ArXiv Preprint,2017

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