Generative Adversarial Network Based Contrast Enhancement: Synthetic Contrast Brain Magnetic Resonance Imaging.

Journal: Academic radiology
PMID: 39694785

Abstract

RATIONALE AND OBJECTIVES: Magnetic resonance imaging (MRI) is a vital tool for diagnosing neurological disorders, frequently utilising gadolinium-based contrast agents (GBCAs) to enhance resolution and specificity. However, GBCAs present certain risks, including side effects, increased costs, and repeated exposure. This study proposes an innovative approach using generative adversarial networks (GANs) for virtual contrast enhancement in brain MRI, with the aim of reducing or eliminating GBCAs, minimising associated risks, and enhancing imaging efficiency while preserving diagnostic quality.

Authors

  • Merve Solak
    Department of Radiology, Recep Tayyip Erdogan University, Rize 53100, Turkey.
  • Murat Tören
    Recep Tayyip Erdogan University, Department of Electrical and Electronics Engineering, Rize, Turkey (M.T., B.A.).
  • Berkutay Asan
    Recep Tayyip Erdogan University, Department of Electrical and Electronics Engineering, Rize, Turkey (M.T., B.A.).
  • Esat Kaba
    Radiology, Recep Tayyip Erdoğan Education and Research Hospital, Rize, TUR.
  • Mehmet Beyazal
    Recep Tayyip Erdogan University, Department of Radiology, Rize.
  • Fatma Beyazal Çeliker
    Department of Radiology, Recep Tayyip Erdogan University, Rize 53100, Turkey.

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