Deep Learning-aided <sup>1</sup>H-MR Spectroscopy for Differentiating between Patients with and without Hepatocellular Carcinoma
Deep-learning-aided <sup>1</sup>H-MRS with data augmentation by spectral simulation may have potential in differentiating between HBV-LC patients with and without HCC.
Authors
- In Chan Song (ORCID: https://orcid.org/0000-0002-5357-5751)
- Jae Seok Bae (ORCID: https://orcid.org/0000-0003-2768-7917)
- Joon Koo Han (ORCID: https://orcid.org/0000-0001-5916-5545)
- Hyeong Hun Lee (ORCID: https://orcid.org/0009-0009-5743-6087)
- Jae‐Young Lee (ORCID: https://orcid.org/0000-0003-2394-5894)
- Hyeonjin Kim (ORCID: https://orcid.org/0000-0001-6862-3907)
Institutions
- Seoul National University (KR)
- Seoul Metropolitan Government (KR)
- New Generation University College (ET)
- Seoul National University Hospital (KR)
- Nano Technology Research Association (KR)
Publication Details
- Journal
- Magnetic Resonance in Medical Sciences
- Published
- 2025-01-01
- DOI
- https://doi.org/10.2463/mrms.mp.2025-0064
- Citations
- 2
- Primary Topic
- Metabolomics and Mass Spectrometry Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.61
Funders
- National Research Foundation
- Seoul National University
- National Research Foundation of Korea
- Seoul National University Hospital
- Ministry of Science and ICT, South Korea
- College of Medicine, Seoul National University