Deep Learning for Image-based Cancer Detection and Diagnosis − A survey
Document Type
Article
Publication Date
11-1-2018
Department
Department of Biomedical Engineering; Department of Applied Computing; Department of Computer Science
Abstract
In this paper, we aim to provide a survey on the applications of deep learning for cancer detection and diagnosis and hope to provide an overview of the progress in this field. In the survey, we firstly provide an overview on deep learning and the popular architectures used for cancer detection and diagnosis. Especially we present four popular deep learning architectures, including convolutional neural networks, fully convolutional networks, auto-encoders, and deep belief networks in the survey. Secondly, we provide a survey on the studies exploiting deep learning for cancer detection and diagnosis. The surveys in this part are organized based on the types of cancers. Thirdly, we provide a summary and comments on the recent work on the applications of deep learning to cancer detection and diagnosis and propose some future research directions.
Publication Title
Pattern Recognition
Recommended Citation
Hu, Z.,
Tang, J.,
Wang, Z.,
Zhang, K.,
Zhang, L.,
&
Sun, Q.
(2018).
Deep Learning for Image-based Cancer Detection and Diagnosis − A survey.
Pattern Recognition,
83, 134-149.
http://doi.org/10.1016/j.patcog.2018.05.014
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/6964
Publisher's Statement
© 2018 Published by Elsevier Ltd.