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Feasibility of Dedicated Breast Positron Emission Tomography Image Denoising Using a Residual Neural Network
OBJECTIVE(S): This study aimed to create a deep learning (DL)-based denoising model using a residual neural network (Res-Net) trained to reduce noise in ring-type dedicated breast positron emission tomography (dbPET) images acquired in about half the emission time, and to evaluate the feasibility an...
Autores principales: | Itagaki, Koji, Miyake, Kanae K., Tanoue, Minori, Oishi, Tae, Kataoka, Masako, Kawashima, Masahiro, Toi, Masakazu, Nakamoto, Yuji |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Mashhad University of Medical Sciences
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10261694/ https://www.ncbi.nlm.nih.gov/pubmed/37324225 http://dx.doi.org/10.22038/AOJNMB.2023.71598.1501 |
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