Wasserstein K-Means for Clustering Tomographic Projections
@article{Rao2020WassersteinKF, title={Wasserstein K-Means for Clustering Tomographic Projections}, author={Rohan Rao and Amit Moscovich and A. Singer}, journal={ArXiv}, year={2020}, volume={abs/2010.09989} }
Motivated by the 2D class averaging problem in single-particle cryo-electron microscopy (cryo-EM), we present a k-means algorithm based on a rotationally-invariant Wasserstein metric for images. Unlike existing methods that are based on Euclidean ($L_2$) distances, we prove that the Wasserstein metric better accommodates for the out-of-plane angular differences between different particle views. We demonstrate on a synthetic dataset that our method gives superior results compared to an $L_2… CONTINUE READING
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