Deep Volumetric Descriptor Learning for Dense Correspondence of Cone-Beam Computed Tomography via Spectral Maps-Reference-Cited by-同舟云学术

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Deep Volumetric Descriptor Learning for Dense Correspondence of Cone-Beam Computed Tomography via Spectral Maps

Published:2022-08 Issue:8 Volume:41 Page:2157-2169
ISSN:0278-0062
Container-title:IEEE Transactions on Medical Imaging
language:
Short-container-title:IEEE Trans. Med. Imaging

Author:

Sun Diya¹^ORCID,Zhang Yungeng²,Pei Yuru²^ORCID,Li Peixin²,Nie Kaichen²^ORCID,Xu Tianmin³,Wang Tianbing⁴,Zha Hongbin²^ORCID

Affiliation:

1. Department of Machine Intelligence, School of Artificial Intelligence, Key Laboratory of Machine Perception (MOE), Institute for Artificial Intelligence, Peking University People’s Hospital, Peking University, Beijing, China

2. Department of Machine Intelligence, School of Artificial Intelligence, Key Laboratory of Machine Perception (MOE), Peking University, Beijing, China

3. School of Stomatology, Stomatology Hospital, Peking University, Beijing, China

4. Trauma Medicine Center, Peking University People’s Hospital, Peking University, Beijing, China

Funder

National Natural Science Foundation of China

National Key Technologies Research and Development Program (NKTRDP) China

Beijing Natural Science Foundation

Research Center of Engineering and Technology for Digital Dentistry, Ministry of Health

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Radiological and Ultrasound Technology,Software

Link

http://xplorestaging.ieee.org/ielx7/42/9847115/09730858.pdf?arnumber=9730858

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