OFF-eNET: An Optimally Fused Fully End-to-End Network for Automatic Dense Volumetric 3D Intracranial Blood Vessels Segmentation-Reference-Cited by-同舟云学术

OFF-eNET: An Optimally Fused Fully End-to-End Network for Automatic Dense Volumetric 3D Intracranial Blood Vessels Segmentation

Published:2020 Issue: Volume:29 Page:7192-7202
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Nazir Anam,Cheema Muhammad Nadeem^ORCID,Sheng Bin^ORCID,Li Huating,Li Ping^ORCID,Yang Po^ORCID,Jung Younhyun^ORCID,Qin Jing^ORCID,Kim Jinman^ORCID,Feng David Dagan^ORCID

Funder

National Natural Science Foundation of China

Science and Technology Commission of Shanghai Municipality

Hong Kong Research Grants Council

The Hong Kong Polytechnic University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/8835130/09112643.pdf?arnumber=9112643

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