Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-26T12:35:06.415Z Has data issue: false hasContentIssue false

CryoDiscoveryTM: A Machine Learning Platform for Automated Cryo-electron Microscopy Particle Classification

Published online by Cambridge University Press:  30 July 2020

Narasimha Kumar
Affiliation:
Health Technology Innovations, Portland, Oregon, United States
John Harkness
Affiliation:
Rewire Neuroscience, Portland, Oregon, United States
Craig Yoshioka
Affiliation:
Oregon Health & Science University, Portland, Oregon, United States
Shiva Aditham
Affiliation:
Health Technology Innovations, Portland, Oregon, United States
Tuan Phamdo
Affiliation:
Health Technology Innovations, Portland, Oregon, United States
Kennedy Brown
Affiliation:
Health Technology Innovations, Portland, Oregon, United States

Abstract

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Image Processing Developments in Cryo-EM
Copyright
Copyright © Microscopy Society of America 2020

References

Schapire, R., A Brief Introduction to Boosting. Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, 1999.Google Scholar
Liao, H.Y. and Frank, J., Definition and estimation of resolution in single-particle reconstructions. Structure, 2010. 18(7): p. 768-775.10.1016/j.str.2010.05.008CrossRefGoogle ScholarPubMed
Ndajah, P., et al. SSIM image quality metric for denoised images. in Proc. 3rd WSEAS Int. Conf. on Visualization, Imaging and Simulation. 2010.Google Scholar
Brunet, D., A study of the structural similarity image quality measure with applications to image processing. 2012.Google Scholar