Cargando…
GL-Segnet: Global-Local representation learning net for medical image segmentation
Medical image segmentation has long been a compelling and fundamental problem in the realm of neuroscience. This is an extremely challenging task due to the intensely interfering irrelevant background information to segment the target. State-of-the-art methods fail to consider simultaneously address...
Autores principales: | Gai, Di, Zhang, Jiqian, Xiao, Yusong, Min, Weidong, Chen, Hui, Wang, Qi, Su, Pengxiang, Huang, Zheng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10106565/ https://www.ncbi.nlm.nih.gov/pubmed/37077320 http://dx.doi.org/10.3389/fnins.2023.1153356 |
Ejemplares similares
-
SM-SegNet: A Lightweight Squeeze M-SegNet for Tissue Segmentation in Brain MRI Scans
por: Yamanakkanavar, Nagaraj, et al.
Publicado: (2022) -
Retinal Vessel Automatic Segmentation Using SegNet
por: Xu, Xiaomei, et al.
Publicado: (2022) -
Retracted: Retinal Vessel Automatic Segmentation Using SegNet
por: Methods in Medicine, Computational and Mathematical
Publicado: (2023) -
RMTF-Net: Residual Mix Transformer Fusion Net for 2D Brain Tumor Segmentation
por: Gai, Di, et al.
Publicado: (2022) -
Brain SegNet: 3D local refinement network for brain lesion segmentation
por: Hu, Xiaojun, et al.
Publicado: (2020)