Deep Learning-based Image Enhancement Techniques for Fast MRI in Neuroimaging

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  • Yoo Roh-Eul
    Department of Radiology, National Cancer Center, Goyang-si, Republic of Korea Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
  • Choi Seung Hong
    Department of Radiology, National Cancer Center, Goyang-si, Republic of Korea Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea Center for Nanoparticle Research, Institute for Basic Science (IBS), Seoul, Republic of Korea

Abstract

<p>Despite its superior soft tissue contrast and non-invasive nature, MRI requires long scan times due to its intrinsic signal acquisition principles, a main drawback which technological advancements in MRI have been focused on. In particular, scan time reduction is a natural requirement in neuroimaging due to detailed structures requiring high resolution imaging and often volumetric (3D) acquisitions, and numerous studies have recently attempted to harness deep learning (DL) technology in enabling scan time reduction and image quality improvement. Various DL-based image reconstruction products allow for additional scan time reduction on top of existing accelerated acquisition methods without compromising the image quality.</p>

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