Comprehensive analysis of lung cancer pathology images to discover tumor shape and boundary features that predict survival outcome

Pathology images capture tumor histomorphological details in high resolution. However, manual detection and characterization of tumor regions in pathology images is labor intensive and subjective. Using a deep convolutional neural network (CNN), we developed an automated tumor region recognition sys...

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Detalles Bibliográficos
Autores principales: Wang, Shidan, Chen, Alyssa, Yang, Lin, Cai, Ling, Xie, Yang, Fujimoto, Junya, Gazdar, Adi, Xiao, Guanghua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039531/
https://www.ncbi.nlm.nih.gov/pubmed/29991684
http://dx.doi.org/10.1038/s41598-018-27707-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039531/
https://www.ncbi.nlm.nih.gov/pubmed/29991684
http://dx.doi.org/10.1038/s41598-018-27707-4

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