A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit <a rel="external noopener" href="https://arxiv.org/pdf/2101.03549v1.pdf">the original URL</a>. The file type is <code>application/pdf</code>.
Learning Rotation Invariant Features for Cryogenic Electron Microscopy Image Reconstruction
[article]
<span title="2021-01-10">2021</span>
<i >
arXiv
</i>
<span class="release-stage" >pre-print</span>
Preserved Fulltext
Cryo-Electron Microscopy (Cryo-EM) is a Nobel prize-winning technology for determining the 3D structure of particles at near-atomic resolution. A fundamental step in the recovering of the 3D single-particle structure is to align its 2D projections; thus, the construction of a canonical representation with a fixed rotation angle is required. Most approaches use discrete clustering which fails to capture the continuous nature of image rotation, others suffer from low-quality image reconstruction.
<span class="external-identifiers">
<a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2101.03549v1">arXiv:2101.03549v1</a>
<a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gqbfz62nczbxldcabsddqqwwye">fatcat:gqbfz62nczbxldcabsddqqwwye</a>
</span>
more »
... We propose a novel method that leverages the recent development in the generative adversarial networks. We introduce an encoder-decoder with a rotation angle classifier. In addition, we utilize a discriminator on the decoder output to minimize the reconstruction error. We demonstrate our approach with the Cryo-EM 5HDB and the rotated MNIST datasets showing substantial improvement over recent methods.
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210119052839/https://arxiv.org/pdf/2101.03549v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext">
<button class="ui simple right pointing dropdown compact black labeled icon button serp-button">
<i class="icon ia-icon"></i>
Web Archive
[PDF]
<div class="menu fulltext-thumbnail">
<img src="https://blobs.fatcat.wiki/thumbnail/pdf/02/17/0217f41f52acf6412f6cd6c896504e52b09c6281.180px.jpg" alt="fulltext thumbnail" loading="lazy">
</div>
</button>
</a>
<a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2101.03549v1" title="arxiv.org access">
<button class="ui compact blue labeled icon button serp-button">
<i class="file alternate outline icon"></i>
arxiv.org
</button>
</a>