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	<title>2025Debarnot IceTide - Revision history</title>
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	<updated>2026-06-13T12:14:00Z</updated>
	<subtitle>Revision history for this page on the wiki</subtitle>
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	<entry>
		<id>https://3demmethods.i2pc.es/index.php?title=2025Debarnot_IceTide&amp;diff=4921&amp;oldid=prev</id>
		<title>WikiSysop: Created page with &quot;== Citation ==  V. Debarnot, V. Kishore, R. D. Righetto, and I. Dokmanic, “Ice-tide: Implicit cryo-et imaging and deformation estimation,” IEEE Transactions on Computational Imaging, vol. 11, pp. 24–35, 2025.  == Abstract ==  We introduce ICE-TIDE, amethod for cryogenic electron tomography (cryo-ET) that simultaneously aligns observations and reconstructs a high-resolution volume. The alignment of tilt series in cryo-ET is a major problem limiting the resolution of...&quot;</title>
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		<updated>2025-01-20T06:36:39Z</updated>

		<summary type="html">&lt;p&gt;Created page with &amp;quot;== Citation ==  V. Debarnot, V. Kishore, R. D. Righetto, and I. Dokmanic, “Ice-tide: Implicit cryo-et imaging and deformation estimation,” IEEE Transactions on Computational Imaging, vol. 11, pp. 24–35, 2025.  == Abstract ==  We introduce ICE-TIDE, amethod for cryogenic electron tomography (cryo-ET) that simultaneously aligns observations and reconstructs a high-resolution volume. The alignment of tilt series in cryo-ET is a major problem limiting the resolution of...&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;
V. Debarnot, V. Kishore, R. D. Righetto, and I. Dokmanic, “Ice-tide: Implicit cryo-et imaging and deformation estimation,” IEEE Transactions on Computational Imaging, vol. 11, pp. 24–35, 2025.&lt;br /&gt;
&lt;br /&gt;
== Abstract ==&lt;br /&gt;
&lt;br /&gt;
We introduce ICE-TIDE, amethod for cryogenic electron&lt;br /&gt;
tomography (cryo-ET) that simultaneously aligns observations&lt;br /&gt;
and reconstructs a high-resolution volume. The alignment of&lt;br /&gt;
tilt series in cryo-ET is a major problem limiting the resolution of&lt;br /&gt;
reconstructions. ICE-TIDE relies on an efficient coordinate-based&lt;br /&gt;
implicit neural representation of the volume which enables it to&lt;br /&gt;
directly parameterize deformations and align the projections. Furthermore,&lt;br /&gt;
the implicit network acts as an effective regularizer, allowing&lt;br /&gt;
for high-quality reconstruction at low signal-to-noise ratios&lt;br /&gt;
as well as partially restoring the missing wedge information. We&lt;br /&gt;
compare the performance of ICE-TIDE to existing approaches on&lt;br /&gt;
realistic simulated volumeswhere the significant gains in resolution&lt;br /&gt;
and accuracy of recovering deformations can be precisely evaluated.&lt;br /&gt;
Finally, we demonstrate ICE-TIDE’s ability to perform on&lt;br /&gt;
experimental data sets.&lt;br /&gt;
&lt;br /&gt;
== Keywords ==&lt;br /&gt;
&lt;br /&gt;
== Links ==&lt;br /&gt;
&lt;br /&gt;
https://ieeexplore.ieee.org/abstract/document/10811935&lt;br /&gt;
&lt;br /&gt;
== Related software ==&lt;br /&gt;
&lt;br /&gt;
== Related methods ==&lt;br /&gt;
&lt;br /&gt;
== Comments ==&lt;/div&gt;</summary>
		<author><name>WikiSysop</name></author>
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