Evidence map›Paper›PMID 41108664›Full record

ArticleMagnetic resonance in medicine2026

Online Spatiotemporally Constrained Reconstruction for Real-Time Interactive MRI.

Duc H Le, Prakash Kumar, Ecrin Yagiz, Ye Tian, Krishna S Nayak

Abstract read
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In one paragraph

Article in Magnetic resonance in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
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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.

Duc H LeMing Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.ORCID https://orcid.org/0009-0005-7106-7258
Prakash KumarMing Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.ORCID https://orcid.org/0000-0002-0685-5160
Ecrin YagizMing Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.ORCID https://orcid.org/0000-0001-8113-2192
Ye TianMing Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.ORCID https://orcid.org/0000-0002-8559-4404
Krishna S NayakMing Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.ORCID https://orcid.org/0000-0001-5735-3550

Funding

Volumetric Real-Time MRI at 0.55 TeslaU01HL167613 · NHLBI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Adrienne Campbell, Krishna Shrinivas Nayak · 2023 to 2026
$2.0M
NHLBI NIH HHS U01 HL167613NIH HHS U01-HL167613
6 · The paper itself

Abstract

purposeTo develop a low-latency dynamic MRI reconstruction that provides better spatial and temporal fidelity than contemporary online reconstruction, for localization.

methodsWe utilize online spatiotemporally constrained reconstruction (STCR) using a computationally efficient augmented Lagrangian solution and a limited number of iterations that terminate before the acquisition of the next frame. Online STCR is evaluated in the setting of fetal cardiac localization at 0.55 T, and is compared with online view-sharing and offline compressed sensing, using edge sharpness metrics.

resultsOnline STCR has the highest structural similarity index measure (SSIM) to offline STCR among the compared online reconstruction methods. Spatial edge sharpness improved by 13%

conclusionWe demonstrate low-latency reconstruction for 2D real-time MRI at 1.5

Indexed as

Fetal HeartImage Processing, Computer-AssistedMagnetic Resonance ImagingAlgorithmsFemaleHumansReproducibility of Resultscompressed sensingimage reconstructionlow‐latency reconstructionreal‐time MRI

Identifiers

PMID41108664
PMCPMC12746365

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Registered trials

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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.