Exploring nonlinear feature space dimension reduction and data representation in breast CADx with Laplacian eigenmaps and ‐SNE-Reference-Cited by-同舟云学术

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Exploring nonlinear feature space dimension reduction and data representation in breast CADx with Laplacian eigenmaps and ‐SNE

Published:2009-12-22 Issue:1 Volume:37 Page:339-351
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Jamieson Andrew R.¹,Giger Maryellen L.¹,Drukker Karen¹,Li Hui¹,Yuan Yading¹,Bhooshan Neha¹

Affiliation:

1. Department of Radiology, University of Chicago, Chicago, Illinois 60637

Funder

U.S. Department of Defense

National Institutes of Health

U.S. Department of Energy

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1118/1.3267037

Reference44 articles.

1. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation

2. Visualizing data using ‐SNE;van der Maaten L.;J. Mach. Learn. Res.,2008

3. Anniversary Paper: History and status of CAD and quantitative image analysis: The role ofMedical Physicsand AAPM

4. Automated computerized classification of malignant and benign masses on digitized mammograms

5. Automated seeded lesion segmentation on digital mammograms

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