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...

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Detalles Bibliográficos
Autores principales: Yamanakkanavar, Nagaraj, Choi, Jae Young, Lee, Bumshik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
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

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9104396/
https://www.ncbi.nlm.nih.gov/pubmed/35591129
http://dx.doi.org/10.3390/s22093440

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