ArticlePhysics in medicine and biology2026
Hybrid learning: a combination of self-supervised and supervised learning for joint MRI reconstruction and denoising in low-field MRI.
Haoyang Pei, Nikola Janjušević, Renqing Luo, Ding Xia, Xiang Xu, William Moore, Yao Wang, Hersh Chandarana, Li Feng
Abstract read
In one paragraphArticle in Physics in medicine and biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 · Who and what moneyAuthors and funding
9 authors.
Haoyang PeiBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States of America.ORCID 0009-0007-9258-673X Nikola JanjuševićBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States of America.
Renqing LuoBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States of America.
Ding XiaBiomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.
Xiang XuBiomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.
William MooreBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States of America.ORCID 0009-0008-5860-3804 Yao WangDepartment of Electrical and Computer Engineering, NYU Tandon School of Engineering, New York, NY, United States of America.
Hersh ChandaranaBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States of America.ORCID 0000-0002-6807-4589 Li FengBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States of America.ORCID 0000-0002-8692-7645 Funding
Rapid Motion-Robust and Easy-to-Use Dynamic Contrast-Enhanced MRI for Liver Perfusion QuantificationR01EB030549 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI FENG, LI · 2021 to 2024
$1.7MRapid Structure-Function MRI of the Lung for Post-COVID-19 ManagementR01EB031083 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI FENG, LI · 2021 to 2021
$1.5MNIBIB NIH HHS R01 EB030549NIBIB NIH HHS R01 EB031083
6 · The paper itselfAbstract
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Indexed as
Image Processing, Computer-AssistedMagnetic Resonance ImagingSignal-To-Noise RatioSupervised Machine LearningHumansdeep learningdenoisinghybrid learninglow-fieldlung MRIreconstructionself-supervised learning
Identifiers
PMID42248205
PMCPMC13338756
What OpenQuestion holds
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