Evidence map›Paper›PMID 41889689›Full record

ArticleIEEE transactions on computational imaging2026

Scan-Adaptive MRI Undersampling Using Neighbor-based Optimization (SUNO).

Siddhant Gautam, Angqi Li, Nicole Seiberlich, Jeffrey A Fessler, Saiprasad Ravishankar

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in IEEE transactions on computational imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Siddhant GautamDepartment of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, MI 48824 USA.
Angqi LiDepartment of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, MI 48824 USA.
Nicole SeiberlichDepartment of Radiology, University of Michigan, Ann Arbor, MI 48109 USA.
Jeffrey A FesslerDepartment of Electrical Engineering and Computer Science and the Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109 USA.
Saiprasad RavishankarDepartment of Computational Mathematics, Science and Engineering and the Department of Biomedical Engineering, Michigan State University, East Lansing, MI 48824 USA.

Funding

Machine Learning-Based Adaptation of Data Sampling and Reconstruction for Efficient Dynamic MRIR21EB030762 · NIBIB · MICHIGAN STATE UNIVERSITY · PI RAVISHANKAR, SAIPRASAD · 2022 to 2023
$427k
NIBIB NIH HHS R21 EB030762
6 · The paper itself

Abstract

Accelerated MRI aims to reduce scan time by acquiring data more efficiently, for example, through optimized pulse sequences or readouts that increase

Indexed as

deep learningimage reconstructioniterative coordinate descentMagnetic resonance imagingnearest neighbor searchsampling pattern optimization

Identifiers

PMID41889689
PMCPMC13015899

What OpenQuestion holds

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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.