Cargando…
Joint optic disc and cup segmentation based on densely connected depthwise separable convolution deep network
BACKGROUND: Glaucoma is an eye disease that causes vision loss and even blindness. The cup to disc ratio (CDR) is an important indicator for glaucoma screening and diagnosis. Accurate segmentation for the optic disc and cup helps obtain CDR. Although many deep learning-based methods have been propos...
Autores principales: | Liu, Bingyan, Pan, Daru, Song, Hui |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7842021/ https://www.ncbi.nlm.nih.gov/pubmed/33509106 http://dx.doi.org/10.1186/s12880-020-00528-6 |
Ejemplares similares
-
A depthwise separable dense convolutional network with convolution block attention module for COVID-19 diagnosis on CT scans
por: Li, Qian, et al.
Publicado: (2021) -
LdsConv: Learned Depthwise Separable Convolutions by Group Pruning
por: Lin, Wenxiang, et al.
Publicado: (2020) -
Joint disc and cup segmentation based on recurrent fully convolutional network
por: Gao, Jing, et al.
Publicado: (2020) -
WMR-DepthwiseNet: A Wavelet Multi-Resolution Depthwise Separable Convolutional Neural Network for COVID-19 Diagnosis
por: Monday, Happy Nkanta, et al.
Publicado: (2022) -
Recognition of Crop Diseases Based on Depthwise Separable Convolution in Edge Computing
por: Gu, Musong, et al.
Publicado: (2020)