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Multiscale and Hierarchical Feature-Aggregation Network for Segmenting Medical Images
We propose an encoder–decoder architecture using wide and deep convolutional layers combined with different aggregation modules for the segmentation of medical images. Initially, we obtain a rich representation of features that span from low to high levels and from small to large scales by stacking...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9104396/ https://www.ncbi.nlm.nih.gov/pubmed/35591129 http://dx.doi.org/10.3390/s22093440 |