Development of Deep Learning with RDA U-Net Network for Bladder Cancer Segmentation

SIMPLE SUMMARY: This study proposed the “Residual-Dense-Attention” (RDA) U-Net model architecture to automatically segment organs and lesions in computed tomography (CT) images. The RDA U-Net used ResBlock and DenseBlock at the encoder. Attention gates were used at the decoder position to help the m...

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Detalles Bibliográficos
Autores principales: Lee, Ming-Chan, Wang, Shao-Yu, Pan, Cheng-Tang, Chien, Ming-Yi, Li, Wei-Ming, Xu, Jin-Hao, Luo, Chi-Hung, Shiue, Yow-Ling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9954660/
https://www.ncbi.nlm.nih.gov/pubmed/36831685
http://dx.doi.org/10.3390/cancers15041343

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9954660/
https://www.ncbi.nlm.nih.gov/pubmed/36831685
http://dx.doi.org/10.3390/cancers15041343

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