An Unsupervised Learning Approach to 3D Rectal MRI Volume Registration

An Unsupervised Learning Approach to 3D Rectal MRI Volume Registration

Accurate alignment of multi-session medical imaging is essential to the analysis of disease progression. By comparing the magnetic resonance imaging (MRI) data captured before and after a course of neoadjuvant chemoradiation (nCRT) treatment, physicians are able to evaluate the tumor response for fu...

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Bibliographic Details
Main Authors: Chi-Jui Ho, Soan T. M. Duong, Yiqian Wang, Chanh D. Tr. Nguyen, Bieu Q. Bui, Steven Q. H. Truong, Truong Q. Nguyen, Cheolhong An
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Magnetic resonance imaging
image registration
rectal cancer
deep learning
convolutional neural network
Online Access:https://ieeexplore.ieee.org/document/9861338/

Internet

https://ieeexplore.ieee.org/document/9861338/

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