Evidence map›Paper›PMID 41892487›Full record

ArticleActa crystallographica. Section D, Structural biology2026

ICECREAM: high-fidelity equivariant cryo-electron tomography.

Vinith Kishore, Valentin Debarnot, Ricardo D Righetto, Benjamin D Engel, Ivan Dokmanić

Abstract read
In one paragraph

Article in Acta crystallographica. Section D, Structural biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Vinith KishoreDepartment of Mathematics and Computer Science, University of Basel, 4051 Basel, Switzerland.
Valentin DebarnotINSA-Lyon, Université Claude Bernard Lyon 1, CNRS, Inserm, CREATIS UMR 5220, U1294, Lyon, France.
Ricardo D RighettoBiozentrum, University of Basel, 4056 Basel, Switzerland.
Benjamin D EngelBiozentrum, University of Basel, 4056 Basel, Switzerland.
Ivan DokmanićDepartment of Mathematics and Computer Science, University of Basel, 4051 Basel, Switzerland.

Funding

HORIZON EUROPE European Research Council 852821
6 · The paper itself

Abstract

Cryo-electron tomography (cryo-ET) visualizes 3D cellular architecture in its near-native state. The various deep-learning methods have improved denoising and artifact correction, but remain challenged by a very low signal-to-noise ratio, a restricted tilt range (`missing wedge') and the lack of ground truth. Here, we present ICECREAM, which bridges earlier self-supervised methods with the recent equivariant imaging framework [Chen et al. (2021), IEEE/CVF International Conference on Computer Vision (ICCV), pp. 4359-4368]. Across diverse experimental datasets, ICECREAM achieves substantially better denoising and more reliable missing-wedge filling than existing methods. ICECREAM can be applied to any tomography problem that provides two statistically independent views of the volume; in cryo-ET these are obtained by dose splitting or angular partitioning of the tilt series. ICECREAM is openly available at https://github.com/swing-research/icecream.

Indexed as

Cryoelectron MicroscopyElectron Microscope TomographyImage Processing, Computer-AssistedImaging, Three-DimensionalAnimalsDeep LearningSignal-To-Noise Ratiocryogenic electron tomographydeep learningmachine learningself-supervised learningtomography

Identifiers

PMID41892487
PMCPMC13044925

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.