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Alzheimer's Association International Conference 2026
July 12-15, 2026 | London, United Kingdom, and Online
3933
Qsm-based Assessment Of Amyloid-ί Deposition Using Transformed Multi-space Channel Representations And Deep Learning
Poster Presenter
Authors
Ryu Koda, Yasuko Tatewaki, Benjamin Thyreau, Hirohito Kan, Minato Satomura, Liying Chen, Naoki Kaneko, Ryutaro Namba, Shuko Nomura, Yumi Takano, Taizen Nakase, Yasuyuki Taki
Affiliations
Institute of Development, Aging and Cancer, Tohoku University, Sendai, Miyagi, Japan, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan, Department of Radiology, University of California, Los Angeles, Los Angeles, CA, USA
Part of Topic
Multi-space transformation of QSM captures complementary spatial representations of amyloid-related imaging features for deep learning, improving cerebral amyloid-β classification and advancing MRI-based assessment toward PET-comparable evaluation.
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