End-to-End Deep-Learning-Based Diagnosis of Benign and Malignant Orbital Tumors on Computed Tomography Images

Determining the nature of orbital tumors is challenging for current imaging interpretation methods, which hinders timely treatment. This study aimed to propose an end-to-end deep learning system to automatically diagnose orbital tumors. A multi-center dataset of 602 non-contrast-enhanced computed to...

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Detalles Bibliográficos
Autores principales: Shao, Ji, Zhu, Jiazhu, Jin, Kai, Guan, Xiaojun, Jian, Tianming, Xue, Ying, Wang, Changjun, Xu, Xiaojun, Sun, Fengyuan, Si, Ke, Gong, Wei, Ye, Juan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9960119/
https://www.ncbi.nlm.nih.gov/pubmed/36836437
http://dx.doi.org/10.3390/jpm13020204

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9960119/
https://www.ncbi.nlm.nih.gov/pubmed/36836437
http://dx.doi.org/10.3390/jpm13020204

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