Cargando…
Accurate classification of lung nodules on CT images using the TransUnet
BACKGROUND: Computed tomography (CT) is an effective way to scan for lung cancer. The classification of lung nodules in CT screening is completely doctor dependent, which has drawbacks, including difficulty classifying tiny nodules, subjectivity, and high false-positive rates. In recent years, deep...
Autores principales: | Wang, Hongfeng, Zhu, Hai, Ding, Lihua |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9760709/ https://www.ncbi.nlm.nih.gov/pubmed/36544802 http://dx.doi.org/10.3389/fpubh.2022.1060798 |
Ejemplares similares
-
P-TransUNet: an improved parallel network for medical image segmentation
por: Chong, Yanwen, et al.
Publicado: (2023) -
Accurate segmentation algorithm of acoustic neuroma in the cerebellopontine angle based on ACP-TransUNet
por: Zhang, Zhuo, et al.
Publicado: (2023) -
nn-TransUNet: An Automatic Deep Learning Pipeline for Heart MRI Segmentation
por: Zhao, Li, et al.
Publicado: (2022) -
EG-TransUNet: a transformer-based U-Net with enhanced and guided models for biomedical image segmentation
por: Pan, Shaoming, et al.
Publicado: (2023) -
A diagnostic classification of lung nodules using multiple-scale residual network
por: Wang, Hongfeng, et al.
Publicado: (2023)