Adversarial learning for deformable registration of brain MR image using a multi-scale fully convolutional network-Reference-Cited by-同舟云学术

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Adversarial learning for deformable registration of brain MR image using a multi-scale fully convolutional network

Published:2019-08 Issue: Volume:53 Page:101562
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Duan Luwen,Yuan Gang,Gong Lun,Fu Tianxiao,Yang Xiaodong,Chen Xinjian,Zheng Jian^ORCID

Funder

the National Natural Science Foundation of China

Jiangsu Science and Technology Department

Suzhou Municipal Science and Technology Bureau

Suzhou Institute of Biomedical Engineering and Technology

Chinese Academy of Sciences

Fudan University-SIBET Medical Engineering Joint Fund

Youth Innovation Promotion Association CAS

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing

Reference47 articles.

1. Multi-atlas based segmentation of brain images: Atlas selection and its effect on accuracy;Aljabar;Neuroimage,2009

2. Assessment of parotid gland dose changes during head and neck cancer radiotherapy using daily megavoltage computed tomography and deformable image registration;Lee;Int. J. Radiat. Oncol. Biol. Phys.,2008

3. Improving registration robustness for image-guided liver surgery in a novel human-to-phantom data framework;Collins;IEEE Trans.Med. Imaging,2017

4. A review of geometric transformations for nonrigid body registration;Holden;IEEE Trans. Med. Imaging,2008

5. Nonrigid registration using free-form deformations: application to breast MR images;Rueckert;IEEE Trans. Med. Imaging,1999

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