A Segmentation Framework With Unsupervised Learning-Based Label Mapper for the Ventricular Target of Intracranial Germ Cell Tumor-Reference-Cited by-同舟云学术

A Segmentation Framework With Unsupervised Learning-Based Label Mapper for the Ventricular Target of Intracranial Germ Cell Tumor

Published:2023-11 Issue:11 Volume:27 Page:5381-5392
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Wang Xianyu¹^ORCID,Liu Shuai²^ORCID,Yang Ne¹^ORCID,Chen Fang³^ORCID,Ma Longfei¹^ORCID,Ning Guochen⁴^ORCID,Zhang Hui¹^ORCID,Qiu Xiaoguang²^ORCID,Liao Hongen¹^ORCID

Affiliation:

1. Department of Biomedical Engineering, Tsinghua University, Beijing, China

2. Department of Radiation Oncology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China

3. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China

4. School of Clinical Medicine, Tsinghua University, Beijing, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Beijing Municipal Natural Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/10311342/10236494.pdf?arnumber=10236494

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5. Fully automated intracranial ventricle segmentation on CT with 2D regional convolutional neural network to estimate ventricular volume

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