Self‐adaption and texture generation: A hybrid loss function for low‐dose CT denoising

BACKGROUND: Deep learning has been successfully applied to low‐dose CT (LDCT) denoising. But the training of the model is very dependent on an appropriate loss function. Existing denoising models often use per‐pixel loss, including mean abs error (MAE) and mean square error (MSE). This ignores the d...

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Detalles Bibliográficos
Autores principales: Wang, Zhenchuan, Liu, Minghui, Cheng, Xuan, Zhu, Jinqi, Wang, Xiaomin, Gong, Haigang, Liu, Ming, Xu, Lifeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Medical Imaging
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10476999/
https://www.ncbi.nlm.nih.gov/pubmed/37571834
http://dx.doi.org/10.1002/acm2.14113

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10476999/
https://www.ncbi.nlm.nih.gov/pubmed/37571834
http://dx.doi.org/10.1002/acm2.14113

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