Evaluation of Unsupervised Deformable Image Registration Using CNN and ViT on 4D-CT

The findings have indicated vision transformer architectures to be more effective than convolutional networks for unsupervised deformable registration on 4D-CT data. Foundation Item: This work is supported by the National Natural Science Foundation of China (No.61801413).

Authors

Peizhi Chen (ORCID: https://orcid.org/0000-0001-7507-8791)
Yifan Guo (ORCID: https://orcid.org/0000-0002-9700-5005)
Jingyao Wang (ORCID: https://orcid.org/0009-0008-8185-9007)
Yan Wang (ORCID: https://orcid.org/0000-0002-5344-1884)

Institutions

Xiamen University of Technology (CN)

Publication Details

Journal: Current Medical Imaging Formerly Current Medical Imaging Reviews
Published: 2025-10-22
DOI: https://doi.org/10.2174/0115734056385097251010051841
Primary Topic: Medical Imaging and Analysis
Type: article
Field-Weighted Citation Impact: 0.00

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article

Evaluation of Unsupervised Deformable Image Registration Using CNN and ViT on 4D-CT

Peizhi Chen, Yifan Guo, Jingyao Wang, Yan Wang

Oct 22, 2025

Current Medical Imaging Formerly Current Medical Imaging Reviews

Medical Imaging and Analysis

article

Evaluation of Unsupervised Deformable Image Registration Using CNN and ViT on 4D-CT

Peizhi Chen, Yifan Guo, Jingyao Wang, Yan Wang

October 22, 2025article en

Abstract

The findings have indicated vision transformer architectures to be more effective than convolutional networks for unsupervised deformable registration on 4D-CT data. Foundation Item: This work is supported by the National Natural Science Foundation of China (No.61801413).

Current Medical Imaging Formerly Current Medical Imaging ReviewsVol. 21

Xiamen University of Technology (CN)

Openalex Percentile: Top 70%

Medical Imaging and Analysis

DOI Open Access PDF OpenAlex

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Evaluation of Unsupervised Deformable Image Registration Using CNN and ViT on 4D-CT — Peizhi Chen, Yifan Guo, et al. · Current Medical Imaging Formerly Current Medical Imaging Reviews (2025) | TGRS Research Map | TGRS