Holistic classification of CT attenuation patterns for interstitial lung diseases via deep convolutional neural networks-Reference-Cited by-同舟云学术

Holistic classification of CT attenuation patterns for interstitial lung diseases via deep convolutional neural networks

Published:2016-06-06 Issue:1 Volume:6 Page:1-6
ISSN:2168-1163
Container-title:Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization
language:en
Short-container-title:Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization

Author:

Gao Mingchen¹,Bagci Ulas²^ORCID,Lu Le¹,Wu Aaron¹,Buty Mario¹,Shin Hoo-Chang¹,Roth Holger¹,Papadakis Georgios Z.¹,Depeursinge Adrien³,Summers Ronald M.¹,Xu Ziyue¹^ORCID,Mollura Daniel J.¹

Affiliation:

1. Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD, USA.

2. Center for Research in Computer Vision, University of Central Florida (UCF), Orlando, FL, USA.

3. Institute of Information Systems, University of Applied Sciences Western Switzerland (HES-SO), Sierre, Switzerland.

Funder

National Institutes of Health

University of Central Florida

Publisher

Informa UK Limited

Subject

Computer Science Applications,Radiology Nuclear Medicine and imaging,Biomedical Engineering,Computational Mechanics

Link

https://www.tandfonline.com/doi/pdf/10.1080/21681163.2015.1124249

Reference16 articles.

1. Mitosis Detection in Breast Cancer Histology Images with Deep Neural Networks

2. Near-Affine-Invariant Texture Learning for Lung Tissue Analysis Using Isotropic Wavelet Frames

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