X-ray Cherenkov-luminescence tomography reconstruction with a three-component deep learning algorithm: Swin transformer, convolutional neural network, and locality module

SIGNIFICANCE: X-ray Cherenkov–luminescence tomography (XCLT) produces fast emission data from megavoltage (MV) x-ray scanning, in which the excitation location of molecules within tissue is reconstructed. However standard filtered backprojection (FBP) algorithms for XCLT sinogram reconstruction can...

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Detalles Bibliográficos
Autores principales: Feng, Jinchao, Zhang, Hu, Geng, Mengfan, Chen, Hanliang, Jia, Kebin, Sun, Zhonghua, Li, Zhe, Cao, Xu, Pogue, Brian W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Photo-Optical Instrumentation Engineers 2023
Materias:
Imaging
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932523/
https://www.ncbi.nlm.nih.gov/pubmed/36818584
http://dx.doi.org/10.1117/1.JBO.28.2.026004

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932523/
https://www.ncbi.nlm.nih.gov/pubmed/36818584
http://dx.doi.org/10.1117/1.JBO.28.2.026004

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