Feature self-calibration network with global-local training strategy for multi-region deformable medical image registration-Reference-Cited by-同舟云学术

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Feature self-calibration network with global-local training strategy for multi-region deformable medical image registration

Published:2022-05-29 Issue:19 Volume:34 Page:17175-17191
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Zheng Zhiyuan^ORCID,Cao Wenming^ORCID,Lian Deliang,Luo Yi^ORCID

Funder

the national natural science foundation of china

the fundamental research foundation of shenzhen

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-022-07365-4.pdf

Reference46 articles.

1. Ashburner J (2007) A fast diffeomorphic image registration algorithm. Neuroimage 38(1):95–113

2. Ashburner J, Friston KJ (2000) Voxel-based morphometry-the methods. Neuroimage 11(6):805–821

3. Brian BA, Charles LE, Murray G, James C (2008) Gee. Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Med image Anal, 12(1):26–41,

4. Huang X, Paragios N, Metaxas DN (2006) Shape registration in implicit spaces using information theory and free form deformations. IEEE Trans Pattern Anal Mach Intell 28(8):1303–1318

5. Avants BB, Tustison N, Song G et al (2009) Advanced normalization tools (ants). Insight J 2(365):1–35

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