Cargando…
TC-Net: Dual coding network of Transformer and CNN for skin lesion segmentation
Skin lesion segmentation has become an essential recent direction in machine learning for medical applications. In a deep learning segmentation network, the convolutional neural network (CNN) uses convolution to capture local information for modeling. However, it ignores the relationship between pix...
Autores principales: | Dong, Yuying, Wang, Liejun, Li, Yongming |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9678318/ https://www.ncbi.nlm.nih.gov/pubmed/36409714 http://dx.doi.org/10.1371/journal.pone.0277578 |
Ejemplares similares
-
FAC-Net: Feedback Attention Network Based on Context Encoder Network for Skin Lesion Segmentation
por: Dong, Yuying, et al.
Publicado: (2021) -
HT-Net: A Hybrid Transformer Network for Fundus Vessel Segmentation
por: Hu, Xiaolong, et al.
Publicado: (2022) -
HMT-Net: Transformer and MLP Hybrid Encoder for Skin Disease Segmentation
por: Yang, Sen, et al.
Publicado: (2023) -
HDC-Net: A hierarchical dilation convolutional network for retinal vessel segmentation
por: Hu, Xiaolong, et al.
Publicado: (2021) -
HEA-Net: Attention and MLP Hybrid Encoder Architecture for Medical Image Segmentation
por: An, Lijing, et al.
Publicado: (2022)