Enhancing the Super-Resolution of Medical Images: Introducing the Deep Residual Feature Distillation Channel Attention Network for Optimized Performance and Efficiency

In the advancement of medical image super-resolution (SR), the Deep Residual Feature Distillation Channel Attention Network (DRFDCAN) marks a significant step forward. This work presents DRFDCAN, a model that innovates traditional SR approaches by introducing a channel attention block that is tailor...

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Detalles Bibliográficos
Autores principales: Umirzakova, Sabina, Mardieva, Sevara, Muksimova, Shakhnoza, Ahmad, Shabir, Whangbo, Taegkeun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10669552/
https://www.ncbi.nlm.nih.gov/pubmed/38002456
http://dx.doi.org/10.3390/bioengineering10111332

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10669552/
https://www.ncbi.nlm.nih.gov/pubmed/38002456
http://dx.doi.org/10.3390/bioengineering10111332

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