https://3demmethods.i2pc.es/index.php?action=history&feed=atom&title=2023Marshall_PCA2023Marshall PCA - Revision history2026-05-24T20:20:59ZRevision history for this page on the wikiMediaWiki 1.44.2https://3demmethods.i2pc.es/index.php?title=2023Marshall_PCA&diff=4343&oldid=prevWikiSysop: Created page with "== Citation == Marshall, Nicholas F. / Mickelin, Oscar / Shi, Yunpeng / Singer, Amit. Fast principal component analysis for cryo-electron microscopy images. 2023. Biological..."2023-06-23T09:34:59Z<p>Created page with "== Citation == Marshall, Nicholas F. / Mickelin, Oscar / Shi, Yunpeng / Singer, Amit. Fast principal component analysis for cryo-electron microscopy images. 2023. Biological..."</p>
<p><b>New page</b></p><div>== Citation ==<br />
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Marshall, Nicholas F. / Mickelin, Oscar / Shi, Yunpeng / Singer, Amit. Fast principal component analysis for cryo-electron microscopy images. 2023. Biological Imaging, Vol. 3, p. e2 <br />
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== Abstract ==<br />
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Principal component analysis (PCA) plays an important role in the analysis of cryo-electron microscopy (cryo-EM)<br />
images for various tasks such as classification, denoising, compression, and ab initio modeling. We introduce a fast<br />
method for estimating a compressed representation of the 2-D covariance matrix of noisy cryo-EM projection images<br />
affected by radial point spread functions that enables fast PCA computation. Our method is based on a new algorithm<br />
for expanding images in the Fourier–Bessel basis (the harmonics on the disk), which provides a convenient way to<br />
handle the effect of the contrast transfer functions. For N images of size LL, our method has time complexity<br />
O(NL3+L4)<br />
and space complexity O(NL2+L3 )<br />
. In contrast to previous work, these complexities are independent of<br />
the number of different contrast transfer functions of the images. We demonstrate our approach on synthetic and<br />
experimental data and show acceleration by factors of up to two orders of magnitude.<br />
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== Keywords ==<br />
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== Links ==<br />
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https://www.cambridge.org/core/journals/biological-imaging/article/fast-principal-component-analysis-for-cryoem-images/DAE19FFFC90D618E36EACBD39251D0AB<br />
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== Related software ==<br />
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== Related methods ==<br />
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== Comments ==</div>WikiSysop