Deep learning-based organ-wise dosimetry of 64Cu-DOTA-rituximab through only one scanning

Deep learning-based organ-wise dosimetry of 64Cu-DOTA-rituximab through only one scanning

Abstract This study aimed to generate a delayed 64Cu-dotatate (DOTA)-rituximab positron emission tomography (PET) image from its early-scanned image by deep learning to mitigate the inconvenience and cost of estimating absorbed radiopharmaceutical doses. We acquired PET images from six patients with...

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Bibliographic Details
Main Authors: Kangsan Kim, Jingyu Yang, Muath Almaslamani, Chi Soo Kang, Inki Lee, Ilhan Lim, Sang-Keun Woo
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Scientific Reports
Subjects:
Dosimetry
Deep learning
I2I
GAN
64Cu-DOTA-rituximab
Online Access:https://doi.org/10.1038/s41598-025-88498-z

Internet

https://doi.org/10.1038/s41598-025-88498-z

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