Robust whole slide image analysis for cervical cancer screening using deep learning
Computer-assisted diagnosis is key for scaling up cervical cancer screening, but current algorithms perform poorly on whole slide image analysis and generalization. Here, the authors present a WSI classification and top lesion cell recommendation system using deep learning, and achieve comparable re...
Guardado en:
Autores principales: | Shenghua Cheng, Sibo Liu, Jingya Yu, Gong Rao, Yuwei Xiao, Wei Han, Wenjie Zhu, Xiaohua Lv, Ning Li, Jing Cai, Zehua Wang, Xi Feng, Fei Yang, Xiebo Geng, Jiabo Ma, Xu Li, Ziquan Wei, Xueying Zhang, Tingwei Quan, Shaoqun Zeng, Li Chen, Junbo Hu, Xiuli Liu |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/22c2f657a4034084a68ccb9d935f6590 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
StainNet: A Fast and Robust Stain Normalization Network
por: Hongtao Kang, et al.
Publicado: (2021) -
Sliding of coherent twin boundaries
por: Zhang-Jie Wang, et al.
Publicado: (2017) -
Interpretable Diagnosis for Whole-Slide Melanoma Histology Images Using Convolutional Neural Network
por: Peizhen Xie, et al.
Publicado: (2021) -
Automated Diagnosis and Localization of Melanoma from Skin Histopathology Slides Using Deep Learning: A Multicenter Study
por: Tao Li, et al.
Publicado: (2021) -
Robust fuzzy sliding mode controller for a skid-steered vehicle subjected to friction variations.
por: Yasir Mehmood, et al.
Publicado: (2021)