Cargando…
PyConvU-Net: a lightweight and multiscale network for biomedical image segmentation
BACKGROUND: With the development of deep learning (DL), more and more methods based on deep learning are proposed and achieve state-of-the-art performance in biomedical image segmentation. However, these methods are usually complex and require the support of powerful computing resources. According t...
Autores principales: | Li, Changyong, Fan, Yongxian, Cai, Xiaodong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788933/ https://www.ncbi.nlm.nih.gov/pubmed/33413088 http://dx.doi.org/10.1186/s12859-020-03943-2 |
Ejemplares similares
-
Segmentation of roots in soil with U-Net
por: Smith, Abraham George, et al.
Publicado: (2020) -
BCR-UNet: Bi-directional ConvLSTM residual U-Net for retinal blood vessel segmentation
por: Yi, Yugen, et al.
Publicado: (2022) -
Microscopy cell nuclei segmentation with enhanced U-Net
por: Long, Feixiao
Publicado: (2020) -
Multiscale U-Net with Spatial Positional Attention for Retinal Vessel Segmentation
por: Liu, Congjun, et al.
Publicado: (2022) -
ICOSeg: Real-Time ICOS Protein Expression Segmentation from Immunohistochemistry Slides Using a Lightweight Conv-Transformer Network
por: Singh, Vivek Kumar, et al.
Publicado: (2022)