Automatic diagnosis of imbalanced ophthalmic images using a cost-sensitive deep convolutional neural network

BACKGROUND: Ocular images play an essential role in ophthalmological diagnoses. Having an imbalanced dataset is an inevitable issue in automated ocular diseases diagnosis; the scarcity of positive samples always tends to result in the misdiagnosis of severe patients during the classification task. E...

Descripción completa

Detalles Bibliográficos
Autores principales: Jiang, Jiewei, Liu, Xiyang, Zhang, Kai, Long, Erping, Wang, Liming, Li, Wangting, Liu, Lin, Wang, Shuai, Zhu, Mingmin, Cui, Jiangtao, Liu, Zhenzhen, Lin, Zhuoling, Li, Xiaoyan, Chen, Jingjing, Cao, Qianzhong, Li, Jing, Wu, Xiaohang, Wang, Dongni, Wang, Jinghui, Lin, Haotian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5697161/
https://www.ncbi.nlm.nih.gov/pubmed/29157240
http://dx.doi.org/10.1186/s12938-017-0420-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5697161/
https://www.ncbi.nlm.nih.gov/pubmed/29157240
http://dx.doi.org/10.1186/s12938-017-0420-1

Ejemplares similares