Learning Pre- and Post-contrast Representation for Breast Cancer Segmentation in DCE-MRI-Reference-Cited by-同舟云学术

Learning Pre- and Post-contrast Representation for Breast Cancer Segmentation in DCE-MRI

Published:2022-07 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS)
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Author:

Wu Hong¹,Huo Yingwen¹,Pan Yupeng¹,Xu Zeyan²,Huang Rian¹,Xie Yu³,Han Chu²,Liu Zaiyi²,Wang Yi¹

Affiliation:

1. School of Biomedical Engineering, Health Science Center, Shenzhen University,Smart Medical Imaging, Learning and Engineering (SMILE) Lab, Medical UltraSound Image Computing (MUSIC) Lab,Shenzhen,China,518060

2. Guangdong Academy of Medical Sciences,Guangdong Provincial People's Hospital,Department of Radiology,Guangzhou,Guangdong,China

3. The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Center,Yunnan Cancer Hospital,Department of Radiology,Kunming,China

Funder

National Natural Science Foundation of China

National Key R&D Program of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9866947/9866899/09866993.pdf?arnumber=9866993

Reference20 articles.

1. Hierarchical Convolutional Neural Networks for Segmentation of Breast Tumors in MRI With Application to Radiogenomics

2. Dense Encoder-Decoder Network based on Two-Level Context Enhanced Residual Attention Mechanism for Segmentation of Breast Tumors in Magnetic Resonance Imaging