Cargando…
Accurate Neuronal Soma Segmentation Using 3D Multi-Task Learning U-Shaped Fully Convolutional Neural Networks
Neuronal soma segmentation is a crucial step for the quantitative analysis of neuronal morphology. Automated neuronal soma segmentation methods have opened up the opportunity to improve the time-consuming manual labeling required during the neuronal soma morphology reconstruction for large-scale ima...
Autores principales: | Hu, Tianyu, Xu, Xiaofeng, Chen, Shangbin, Liu, Qian |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7860594/ https://www.ncbi.nlm.nih.gov/pubmed/33551758 http://dx.doi.org/10.3389/fnana.2020.592806 |
Ejemplares similares
-
Touching Soma Segmentation Based on the Rayburst Sampling Algorithm
por: Hu, Tianyu, et al.
Publicado: (2017) -
Evaluating robotic-assisted partial nephrectomy surgeons with fully convolutional segmentation and multi-task attention networks
por: Wang, Yihao, et al.
Publicado: (2023) -
A multi-task fully deep convolutional neural network for contactless fingerprint minutiae extraction
por: Zhang, Zhao, et al.
Publicado: (2021) -
Fully automatic wound segmentation with deep convolutional neural networks
por: Wang, Chuanbo, et al.
Publicado: (2020) -
Accurate de novo peptide sequencing using fully convolutional neural networks
por: Liu, Kaiyuan, et al.
Publicado: (2023)