ITR-Net: A Hybrid Deep Learning Architecture for Precise and Efficient Medical Image Registration-Reference-Cited by-同舟云学术

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ITR-Net: A Hybrid Deep Learning Architecture for Precise and Efficient Medical Image Registration

Published:2023-12-08 Issue: Volume:30 Page:1688-1694
ISSN:
Container-title:2023 IEEE 11th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)
language:
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Author:

Yan Yan¹,Su Liyilei¹,Zhou Chengmin¹,Huang Yongzhi¹,Li Jing²,Li Rui¹,Hassan Haseeb¹,Huang Bingding¹

Affiliation:

1. College of Big Data and Internet, Shenzhen Technology University,Shenzhen,China

2. Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University,Department of Pulmonary and Critical Care Medicine,Guangzhou,Guangdong,China

Funder

Educational Commission of Guangdong Province of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10406301/10408741/10409014.pdf?arnumber=10409014

Reference39 articles.

1. A survey of image registration techniques

2. A survey of medical image registration

3. Robust registration for remote sensing images by combining and localizing feature- and area-based methods

4. A review on medical imaging synthesis using deep learning and its clinical applications

5. Medical Image Registration

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