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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
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- 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
抄録
<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>
収録刊行物
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- Magnetic Resonance in Medical Sciences
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Magnetic Resonance in Medical Sciences advpub (0), 2024
日本磁気共鳴医学会
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詳細情報 詳細情報について
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- CRID
- 1390862931515525888
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- ISSN
- 18802206
- 13473182
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- Crossref
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- 抄録ライセンスフラグ
- 使用不可