Evidence map›Paper›PMID 40039561›Full record

ArticleAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference2024

Physics-Driven Deep Learning Reconstruction of Frequency-Modulated Rabi-Encoded Echoes for Faster Accessible MRI.

Mahdi Saberi, Parker Jenkins, Michael Garwood, Mehmet Akcakaya

Abstract read
In one paragraph

Article in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Mahdi Saberi
Parker Jenkins
Michael Garwood
Mehmet Akcakaya

Funding

TRD4 - Ultrahigh Field Engineering and SafetyP41EB027061 · NIBIB · UNIVERSITY OF MINNESOTA · PI Gregory John Metzger, KAMIL UGURBIL · 2019 to 2026
$11.7M
Imaging Human Brain Function with Minimal Mobility Restrictions - Supplement - NeuroethicsU01EB025153 · NIBIB · UNIVERSITY OF MINNESOTA · PI GARWOOD, MICHAEL · 2017 to 2021
$11.2M
Rapid Comprehensive Cardiac MRI Exam for Diagnosis of Coronary Artery DiseaseR01HL153146 · NHLBI · UNIVERSITY OF MINNESOTA · PI AKCAKAYA, MEHMET · 2020 to 2024
$2.5M
Robust and Efficient Learning of High-Resolution Brain MRI Reconstruction from Small Referenceless DataR01EB032830 · NIBIB · UNIVERSITY OF MINNESOTA · PI Mehmet Akcakaya · 2023 to 2026
$2.0M
NHLBI NIH HHS R01 HL153146NIBIB NIH HHS P41 EB027061NIBIB NIH HHS R01 EB032830NIBIB NIH HHS U01 EB025153
6 · The paper itself

Abstract

Magnetic resonance imaging (MRI) is a powerful imaging modality with exceptional soft tissue contrast capabilities, but it is estimated to only serve 10% of the world's population reliably. This lack of access is largely due to the multi-million cost of initial investment, as well as recurring expenses. Radiofrequency (RF) imaging methods present an opportunity to reduce MRI costs by replacing expensive B

Indexed as

Deep LearningImage Processing, Computer-AssistedMagnetic Resonance ImagingAlgorithmsHumansPhysics

Identifiers

PMID40039561
PMCPMC11883187

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.