Denoising approach with deep learning-based reconstruction for neuromelanin-sensitive MRI: image quality and diagnostic performance
2023 · Japanese Journal of Radiology · 31 citations
https://doi.org/10.1007/s11604-023-01452-9
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Sonoko Oshima
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Sonoko Oshima is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Glioma Diagnosis and Treatment & Radiomics and Machine Learning in Medical Imaging & MRI in cancer diagnosis. The author has an h-index of 8, co-authored 53 publications.
ORCID: 0000-0002-1453-3807Papers by this author
worksAccuracy, repeatability, and reproducibility of T1 and T2 relaxation times measurement by 3D magnetic resonance fingerprinting with different dictionary resolutions
2022 · European Radiology · 10 citations
https://doi.org/10.1007/s00330-022-09244-x
Evaluation of isocitrate dehydrogenase mutation in 2021 world health organization classification grade 3 and 4 glioma adult-type diffuse gliomas with 18F-fluoromisonidazole PET
2023 · Japanese Journal of Radiology · 8 citations
https://doi.org/10.1007/s11604-023-01450-x
Multi-nuclear sodium, diffusion, and perfusion MRI in human gliomas
2023 · Journal of Neuro-Oncology · 8 citations
https://doi.org/10.1007/s11060-023-04363-x
Diffusion MRI is superior to quantitative T2-FLAIR mismatch in predicting molecular subtypes of human non-enhancing gliomas
2024 · Neuroradiology · 5 citations
https://doi.org/10.1007/s00234-024-03475-z
Supplemental Figure S1 from Depth of radiographic response (DpR) and time to tumor regrowth (TTG) predicts overall survival following anti-VEGF therapy in recurrent glioblastoma
2024 · 0 citations
https://doi.org/10.1158/1078-0432.27034138
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