Cargando…
A deep learning-based post-processing method for automated pulmonary lobe and airway trees segmentation using chest CT images in PET/CT
BACKGROUND: The proposed algorithm could support accurate localization of lung disease. To develop and validate an automated deep learning model combined with a post-processing algorithm to segment six pulmonary anatomical regions in chest computed tomography (CT) images acquired during positron emi...
Autores principales: | Xing, Haiqun, Zhang, Xin, Nie, Yingbin, Wang, Sicong, Wang, Tong, Jing, Hongli, Li, Fang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9511416/ https://www.ncbi.nlm.nih.gov/pubmed/36185049 http://dx.doi.org/10.21037/qims-21-1116 |
Ejemplares similares
-
Deep learning-based automated segmentation of eight brain anatomical regions using head CT images in PET/CT
por: Wang, Tong, et al.
Publicado: (2022) -
Automatic pulmonary fissure detection and lobe segmentation in CT chest images
por: Qi, Shouliang, et al.
Publicado: (2014) -
Application of Deep Convolution Network to Automated Image Segmentation of Chest CT for Patients With Tumor
por: Xie, Hui, et al.
Publicado: (2021) -
Automated semantic lung segmentation in chest CT images using deep neural network
por: Murugappan, M., et al.
Publicado: (2023) -
Segmentation of lung lobes and lesions in chest CT for the classification of COVID-19 severity
por: Khomduean, Prachaya, et al.
Publicado: (2023)