Accelerated intracranial time-of-flight MR angiography with image-based deep learning image enhancement reduces scan times and improves image quality at 3-T and 1.5-T
Accelerated intracranial MRA with deep learning-based reconstruction reduces scan times by 40% and significantly enhances image quality over conventional TOF-MRA at both 3-T and 1.5-T.
Authors
- Kyu Sung Choi (ORCID: https://orcid.org/0000-0002-5175-3307)
- Roh‐Eul Yoo (ORCID: https://orcid.org/0000-0002-5625-5921)
- Inpyeong Hwang (ORCID: https://orcid.org/0000-0002-1291-8973)
- Tae Jin Yun (ORCID: https://orcid.org/0000-0001-8441-4574)
- Ji Ye Lee (ORCID: https://orcid.org/0000-0002-3929-6254)
- Koung Mi Kang (ORCID: https://orcid.org/0000-0001-9643-2008)
- Kyung Hoon Lee (ORCID: https://orcid.org/0000-0002-4818-2937)
- Young Hun Jeon (ORCID: https://orcid.org/0000-0001-7672-3932)
- Chanrim Park (ORCID: https://orcid.org/0009-0000-2661-7111)
- Chul‐Ho Sohn (ORCID: https://orcid.org/0000-0003-0039-5746)
- Ji‐hoon Kim (ORCID: https://orcid.org/0000-0002-6349-6950)
- Seung Hong Choi
Institutions
- Seoul National University (KR)
- Seoul National University Hospital (KR)
- Kangbuk Samsung Hospital (KR)
Publication Details
- Journal
- Neuroradiology
- Published
- 2025-03-17
- DOI
- https://doi.org/10.1007/s00234-025-03564-7
- Citations
- 3
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 4.08
Funders
- Seoul National University Hospital