Deformable registration of chest CT images using a 3D convolutional neural network based on unsupervised learning.

Journal: Journal of applied clinical medical physics

Published Date: Sep 10, 2021

Abstract

PURPOSE: The deformable registration of 3D chest computed tomography (CT) images is one of the most important tasks in the field of medical image registration. However, the nonlinear deformation and large-scale displacement of lung tissues caused by respiratory motion cause great challenges in the deformable registration of 3D lung CT images.

Authors

Yongnan Zheng

School of Mechanical Engineering, Tianjin University, Tianjin, China.
Shan Jiang

Emergency Center, Hubei Clinical Research Center for Emergency and Resuscitaion, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.
Zhiyong Yang

Keywords

Image Processing, Computer-Assisted Imaging, Three-Dimensional Neural Networks, Computer Tomography, X-Ray Computed Unsupervised Machine Learning

External Resources

View on PubMed Access via DOI PubMed (34505341)

Deformable registration of chest CT images using a 3D convolutional neural network based on unsupervised learning.

Abstract

Authors

Keywords

External Resources

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