Application of AI-driven Image to Image Translation Techniques in Neuroradiology

DOI
  • Takita Hirotaka
    Department of Diagnostic and Interventional Radiology, Graduate School of Medicine, Osaka Metropolitan University
  • Ueda Daiju
    Department of Diagnostic and Interventional Radiology, Graduate School of Medicine, Osaka Metropolitan University

Bibliographic Information

Other Title
  • 人工知能による画像変換技術の神経放射線領域への応用について

Description

<p>In recent years, the rapid evolution of artificial intelligence (AI) has brought about a revolution in medical research. In particular, the application of AI technology to medical imaging is expanding rapidly, with image-to-image translation technique gaining significant attention. Image-to-image translation technique allows for a wide range of applications, such as converting between different imaging modalities and removing artifacts. It is expected to open up new perspectives that go beyond the traditional framework of medical imaging. Using image-to-image translation models, it’s possible to generate synthetic PET from MRI images, or convert images with artifacts to those without, potentially contributing to improved diagnostic accuracy and optimization of treatment plans. In this article, we introduce two papers we published applying image-to-image translation technique in the field of neuroradiology: a study on generating synthetic methionine PET using MRI, and a study on producing Digital Subtraction Angiography (DSA) without misregistration artifacts.</p>

Journal

Keywords

Details 詳細情報について

  • CRID
    1390298588087195392
  • DOI
    10.11318/mii.40.66
  • ISSN
    18804977
    09101543
  • Text Lang
    ja
  • Data Source
    • JaLC
  • Abstract License Flag
    Disallowed

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