Image-to-image generative adversarial networks for synthesizing perfusion parameter maps from dsc-mr images in cerebrovascular disease

HIGHLIGHTS

• who: Tabea Kossen from the University of Alberta, Canada have published the Article: Image-to-image generative adversarial networks for synthesizing perfusion parameter maps from DSC-MR images in cerebrovascular disease, in the Journal: (JOURNAL)
• what: The authors propose a modified slice-wise pix2pix GAN with a temporal component (temp-pix2pix-GAN) to account for the time dimension in DSC source perfusion imaging. The authors implemented two different generator architectures. At this point, it is important to emphasize that the study is exploratory, and the generated model is only used for internal research purposes.
 



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