Spine Computed Tomography to Magnetic Resonance Image Synthesis Using Generative Adversarial Networks : A Preliminary Study

• Published in: Journal of Korean Neurosurgical Society Vol. 63; no. 3; pp. 386 - 396
• Main Authors: Lee, Jung Hwan, Han, In Ho, Kim, Dong Hwan, Yu, Seunghan, Lee, In Sook, Song, You Seon, Joo, Seongsu, Jin, Cheng-Bin, Kim, Hakil
• Format: Journal Article
• Language: English
• Published: Korea (South) Korean Neurosurgical Society 01.05.2020; 대한신경외과학회
• Subjects: Laboratory Investigation; 신경외과학; Deep learning; Computed tomography; Magnetic resonance imaging; Lumbar vertebrae

To generate synthetic spine magnetic resonance (MR) images from spine computed tomography (CT) using generative adversarial networks (GANs), as well as to determine the similarities between synthesized and real MR images. GANs were trained to transform spine CT image slices into spine magnetic reson...