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eess.IVJul 1, 2019
10
citations (OpenAlex)
authors
  • David Abramian
  • Anders Eklund
arXiv abstractPDF
paper

Generating fMRI volumes from T1-weighted volumes using 3D CycleGAN

arXiv:1907.08533

Abstract

Registration between an fMRI volume and a T1-weighted volume is challenging, since fMRI volumes contain geometric distortions. Here we present preliminary results showing that 3D CycleGAN can be used to synthesize fMRI volumes from T1-weighted volumes, and vice versa, which can facilitate registration.

References in corpus (5)

  • Generative Adversarial Network in Medical Imaging: A Review
  • Progressive Growing of GANs for Improved Quality, Stability, and Variation
  • Generative Adversarial Networks for Image-to-Image Translation on Multi-Contrast MR Images - A Comparison of CycleGAN and UNIT
  • Refacing: reconstructing anonymized facial features using GANs
  • Reply to Cox et al. and Kessler et al.: Data and code sharing is the way forward for fMRI

Cited by in corpus (3)

  • Unsupervised-learning-based method for chest MRI-CT transformation using structure constrained unsupervised generative attention networks
  • Feeding the zombies: Synthesizing brain volumes using a 3D progressive growing GAN
  • Synthesizing brain tumor images and annotations by combining progressive growing GAN and SPADE
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