Deformable registration of magnetic resonance images using unsupervised deep learning in neuro-/radiation oncology

Deformable registration of magnetic resonance images using unsupervised deep learning in neuro-/radiation oncology

Abstract Purpose Accurate deformable registration of magnetic resonance imaging (MRI) scans containing pathologies is challenging due to changes in tissue appearance. In this paper, we developed a novel automated three-dimensional (3D) convolutional U-Net based deformable image registration (ConvUNe...

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Bibliographic Details
Main Authors: Alexander F. I. Osman, Kholoud S. Al-Mugren, Nissren M. Tamam, Bilal Shahine
Format: Article
Language:English
Published: BMC 2024-05-01
Series:Radiation Oncology
Subjects:
Deformable image registration
MRI
Convolutional neural networks
Unsupervised learning
Glioma
Neuro-/radiation oncology
Online Access:https://doi.org/10.1186/s13014-024-02452-3

Internet

https://doi.org/10.1186/s13014-024-02452-3

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