A Cascaded Multi-Task Generative Framework for Detecting Aortic Dissection on 3-D Non-Contrast-Enhanced Computed Tomography-Reference-Cited by-同舟云学术

A Cascaded Multi-Task Generative Framework for Detecting Aortic Dissection on 3-D Non-Contrast-Enhanced Computed Tomography

Published:2022-10 Issue:10 Volume:26 Page:5177-5188
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Xiong Xiangyu¹^ORCID,Ding Yan²,Sun Chuanqi¹,Zhang Zhuoneng¹,Guan Xiuhong³,Zhang Tianjing⁴,Chen Hao⁵^ORCID,Liu Hongyan⁶,Cheng Zhangbo⁷,Zhao Lei²,Ma Xiaohai²,Xie Guoxi¹^ORCID

Affiliation:

1. School of Biomedical Engineering, The Sixth Affiliated Hospital, Guangzhou Medical University, Guangzhou, China

2. Department of Interventional Diagnosis and Treatment, Beijing Anzhen Hospital, Capital Medical University, Beijing, China

3. First Clinical Medical College, Jinan University, Guangzhou, China

4. Department of Advanced Technical Support, Philips Healthcare, Guangzhou, China

5. Department of Mathware, Jiangsu JITRI Sioux Technologies Company, Ltd, Suzhou, China

6. Department of Medical Imaging, The Sixth Affiliated Hospital, Guangzhou Medical University, Qingyuan, China

7. Fujian Provincal Clinical College, Fujian Medical University, Fuzhou, Fujian, China

Funder

National Natural Science Foundation of China

Beijing 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/ielx7/6221020/9910251/09827558.pdf?arnumber=9827558

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5. Detection, segmentation, simulation and visualization of aortic dissections: A review

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