2025Debarnot IceTide

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 reconstructions. ICE-TIDE relies on an efficient coordinate-based implicit neural representation of the volume which enables it to directly parameterize deformations and align the projections. Furthermore, the implicit network acts as an effective regularizer, allowing for high-quality reconstruction at low signal-to-noise ratios as well as partially restoring the missing wedge information. We compare the performance of ICE-TIDE to existing approaches on realistic simulated volumeswhere the significant gains in resolution and accuracy of recovering deformations can be precisely evaluated. Finally, we demonstrate ICE-TIDE’s ability to perform on experimental data sets.

Links

https://ieeexplore.ieee.org/abstract/document/10811935