Unsupervised Multi-Discriminator Generative Adversarial Network for Lung Nodule Malignancy Classification

Unsupervised Multi-Discriminator Generative Adversarial Network for Lung Nodule Malignancy Classification

Computer-aided diagnosis systems with deep learning frameworks have been used to identify benign and malignant pulmonary nodules in lung cancer diagnosis. It's commonly known that a premise of training complex deep neural nets is the large-scale labeled datasets. However, the abundance of label...

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Bibliographic Details
Main Authors: Yan Kuang, Tian Lan, Xueqiao Peng, Gati Elvis Selasi, Qiao Liu, Junyi Zhang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Computer-aided diagnosis (CAD)
lung nodule
malignancy classification
unsupervised learning
generative adversarial networks
Online Access:https://ieeexplore.ieee.org/document/9066829/

Internet

https://ieeexplore.ieee.org/document/9066829/

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