Translation of computed tomography images to T2-Weighted magnetic resonance images of lumbar spine using generative adversarial networks on sagittal images

Translation of computed tomography images to T2-Weighted magnetic resonance images of lumbar spine using generative adversarial networks on sagittal images

Abstract This study aims to develop a generative adversarial networks (GAN)-based image translation model for synthesizing lumbar spine Computed Tomography (CT) to Magnetic Resonance (MR) images, focusing on sagittal images, and to evaluate its performance. A cycle-consistent GAN was used to transla...

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Bibliographic Details
Main Authors: Kwang Hyeon Kim, Eun-Chong Lee, Yeo Dong Yoon, Dong-Won Shin, Hae-Won Koo, Byung-Jou Lee
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Generative adversarial networks
Lumbar spine
Computed tomography
Magnetic resonance imaging
Image-to-image translation
Online Access:https://doi.org/10.1038/s41598-025-03516-4
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https://doi.org/10.1038/s41598-025-03516-4

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