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Generalization of Deep Learning Models for Ultra-low-count Amyloid PET/MRI using Transfer Learning

PURPOSE: We aimed to evaluate the performance of deep learning-based generalization of ultra-low-count amyloid PET/MRI enhancement when applied to studies acquired with different scanning hardware and protocols. METHODS: 80 simultaneous [(18)F]florbetaben PET/MRI studies were acquired, split equally...

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Veröffentlicht in:Eur J Nucl Med Mol Imaging
Hauptverfasser: Chen, Kevin T., Schürer, Matti, Ouyang, Jiahong, Koran, Mary Ellen, Davidzon, Guido, Mormino, Elizabeth, Tiepolt, Solveig, Hoffmann, Karl-Titus, Sabri, Osama, Zaharchuk, Greg, Barthel, Henryk
Format: Artigo
Sprache:Inglês
Veröffentlicht: 2020
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Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC7680289/
https://ncbi.nlm.nih.gov/pubmed/32535655
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00259-020-04897-6
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