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	<title>2016Bhamre Denoising - Revision history</title>
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	<entry>
		<id>https://3demmethods.i2pc.es/index.php?title=2016Bhamre_Denoising&amp;diff=3061&amp;oldid=prev</id>
		<title>Amit Singer: Created page with &quot;== Citation ==  Bhamre, T., Zhang, T., &amp; Singer, A. (2016). Denoising and covariance estimation of single particle cryo-EM images. Journal of structural biology, 195(1), 72-81...&quot;</title>
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		<updated>2017-05-05T15:42:24Z</updated>

		<summary type="html">&lt;p&gt;Created page with &amp;quot;== Citation ==  Bhamre, T., Zhang, T., &amp;amp; Singer, A. (2016). Denoising and covariance estimation of single particle cryo-EM images. Journal of structural biology, 195(1), 72-81...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;== Citation ==&lt;br /&gt;
&lt;br /&gt;
Bhamre, T., Zhang, T., &amp;amp; Singer, A. (2016). Denoising and covariance estimation of single particle cryo-EM images. Journal of structural biology, 195(1), 72-81.&lt;br /&gt;
&lt;br /&gt;
== Abstract ==&lt;br /&gt;
&lt;br /&gt;
The problem of image restoration in cryo-EM entails correcting for the effects of the Contrast Transfer&lt;br /&gt;
Function (CTF) and noise. Popular methods for image restoration include &amp;quot;phase flipping&amp;quot;, which corrects&lt;br /&gt;
only for the Fourier phases but not amplitudes, and Wiener filtering, which requires the spectral signal to&lt;br /&gt;
noise ratio. We propose a new image restoration method which we call &amp;quot;Covariance Wiener Filtering&amp;quot;&lt;br /&gt;
(CWF). In CWF, the covariance matrix of the projection images is used within the classical Wiener filtering&lt;br /&gt;
framework for solving the image restoration deconvolution problem. Our estimation procedure for&lt;br /&gt;
the covariance matrix is new and successfully corrects for the CTF. We demonstrate the efficacy of&lt;br /&gt;
CWF by applying it to restore both simulated and experimental cryo-EM images. Results with experimental&lt;br /&gt;
datasets demonstrate that CWF provides a good way to evaluate the particle images and to see what&lt;br /&gt;
the dataset contains even without 2D classification and averaging.&lt;br /&gt;
&lt;br /&gt;
== Keywords ==&lt;br /&gt;
&lt;br /&gt;
CTF correction, Steerable PCA, Wiener filtering&lt;br /&gt;
&lt;br /&gt;
== Links ==&lt;br /&gt;
&lt;br /&gt;
https://www.ncbi.nlm.nih.gov/pubmed/27129418&lt;br /&gt;
&lt;br /&gt;
== Related software ==&lt;br /&gt;
&lt;br /&gt;
ASPIRE&lt;br /&gt;
&lt;br /&gt;
== Related methods ==&lt;br /&gt;
&lt;br /&gt;
== Comments ==&lt;/div&gt;</summary>
		<author><name>Amit Singer</name></author>
	</entry>
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