A fully automatic artificial intelligence–based CT image analysis system for accurate detection, diagnosis, and quantitative severity evaluation of pulmonary tuberculosis

OBJECTIVES: An accurate and rapid diagnosis is crucial for the appropriate treatment of pulmonary tuberculosis (TB). This study aims to develop an artificial intelligence (AI)–based fully automated CT image analysis system for detection, diagnosis, and burden quantification of pulmonary TB. METHODS:...

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Detalles Bibliográficos
Autores principales: Yan, Chenggong, Wang, Lingfeng, Lin, Jie, Xu, Jun, Zhang, Tianjing, Qi, Jin, Li, Xiangying, Ni, Wei, Wu, Guangyao, Huang, Jianbin, Xu, Yikai, Woodruff, Henry C., Lambin, Philippe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Computed Tomography
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628489/
https://www.ncbi.nlm.nih.gov/pubmed/34842959
http://dx.doi.org/10.1007/s00330-021-08365-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628489/
https://www.ncbi.nlm.nih.gov/pubmed/34842959
http://dx.doi.org/10.1007/s00330-021-08365-z

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