Cargando…
Development of a deep learning model for classifying thymoma as Masaoka-Koga stage I or II via preoperative CT images
BACKGROUND: Accurate thymoma staging via computed tomography (CT) images is difficult even for experienced thoracic doctors. Here we developed a preoperative staging tool differentiating Masaoka-Koga (MK) stage I patients from stage II patients using CT images. METHODS: CT images of 174 thymoma pati...
Autores principales: | Yang, Lei, Cai, Wenjia, Yang, Xiaoyu, Zhu, Haoshuai, Liu, Zhenguo, Wu, Xi, Lei, Yiyan, Zou, Jianyong, Zeng, Bo, Tian, Xi, Zhang, Rongguo, Luo, Honghe, Zhu, Ying |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7186715/ https://www.ncbi.nlm.nih.gov/pubmed/32355731 http://dx.doi.org/10.21037/atm.2020.02.183 |
Ejemplares similares
-
Impact of Definitive Radiotherapy and Surgical Debulking on Treatment Outcome and Prognosis for Locally Advanced Masaoka-Koga stage III Thymoma
por: Fan, Chengcheng, et al.
Publicado: (2020) -
Relationship Between Computed Tomography Imaging Features and Clinical Characteristics, Masaoka–Koga Stages, and World Health Organization Histological Classifications of Thymoma
por: Han, Xiaowei, et al.
Publicado: (2019) -
Predicting Masaoka-Koga Clinical Stage of Thymic Epithelial Tumors Using Preoperative Spectral Computed Tomography Imaging
por: Zhou, Qing, et al.
Publicado: (2021) -
胸腺恶性肿瘤Masaoka-Koga分期相关术语的说明与定义
por: Detterbeck, Frank C., et al.
Publicado: (2014) -
3D DenseNet Deep Learning Based Preoperative Computed Tomography for Detecting Myasthenia Gravis in Patients With Thymoma
por: Liu, Zhenguo, et al.
Publicado: (2021)