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R2U++: a multiscale recurrent residual U-Net with dense skip connections for medical image segmentation
U-Net is a widely adopted neural network in the domain of medical image segmentation. Despite its quick embracement by the medical imaging community, its performance suffers on complicated datasets. The problem can be ascribed to its simple feature extracting blocks: encoder/decoder, and the semanti...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer London
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9165712/ https://www.ncbi.nlm.nih.gov/pubmed/35694048 http://dx.doi.org/10.1007/s00521-022-07419-7 |