Evidence map›Paper›PMID 40881624›Full record

ArticleProceedings. IEEE International Symposium on Biomedical Imaging2025

FAST MULTI-CONTRAST MRI USING JOINT MULTISCALE ENERGY MODEL.

Nima Yaghoobi, Jyothi Rikhab Chand, Yan Chen, Steve R Kecskemeti, James H Holmes, Mathews Jacob

Abstract read
In one paragraph

Article in Proceedings. IEEE International Symposium on Biomedical Imaging, 2025. 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

6 authors.

Nima YaghoobiUniversity of Virginia.
Jyothi Rikhab ChandUniversity of Virginia.
Yan ChenUniversity of Virginia.
Steve R KecskemetiUniversity of Wisconsin-Madison.
James H HolmesUniversity of Iowa.
Mathews JacobUniversity of Virginia.

Funding

University of Iowa Hawkeye Intellectual and Developmental Disabilities Research Center (Hawk-IDDRC)P50HD103556 · NICHD · UNIVERSITY OF IOWA · PI EDWIN TED G. ABEL, Lane Strathearn · 2021 to 2026
$8.5M
Novel Computational Framework for Free-Breathing & Ungated Dynamic MRIR01EB019961 · NIBIB · UNIVERSITY OF VIRGINIA · PI Mathews Jacob · 2016 to 2026
$4.0M
Model Based Deep Learning Framework for Ultra-High Resolution Multi-Contrast MRIR01AG067078 · NIA · UNIVERSITY OF VIRGINIA · PI JACOB, MATHEWS · 2021 to 2025
$3.4M
Motion Robust Relaxometry for Infant NeuroimagingR01HD108868 · NICHD · UNIVERSITY OF WISCONSIN-MADISON · PI ALEXANDER, ANDREW L, GILLICK, BERNADETTE THERESE · 2022 to 2025
$2.5M
High Resolution MRSI for Alzheimer's Disease and Related DementiasR01AG087159 · NIA · UNIVERSITY OF IOWA · PI Mathews Jacob, Yan Li · 2024 to 2026
$2.3M
NIA NIH HHS R01 AG067078NIA NIH HHS R01 AG087159NIBIB NIH HHS R01 EB019961NICHD NIH HHS P50 HD103556NICHD NIH HHS R01 HD108868
6 · The paper itself

Abstract

The acquisition of 3D multicontrast MRI data with good isotropic spatial resolution is challenged by lengthy scan times. In this work, we introduce a CNN-based multiscale energy model to learn the joint probability distribution of the multi-contrast images. The joint recovery of the contrasts from undersampled data is posed as a maximum a posteriori estimation scheme, where the learned energy serves as the prior. We use a majorize-minimize algorithm to solve the optimization scheme. The proposed model leverages the redundancies across different contrasts to improve image fidelity. The proposed scheme is observed to preserve fine details and contrast, offering sharper reconstructions compared to reconstruction methods that independently recover the contrasts. While we focus on 3D MPNRAGE acquisitions in this work, the proposed approach is generalizable to arbitrary multi-contrast settings.

Indexed as

Energy based modelPlug-and-playReconstruction

Identifiers

PMID40881624
PMCPMC12381937

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.