Evidence map›Paper›PMID 42370237›Full record

ArticleResearch square2026

MRecover: A Conditional Generative Model for Recovering Motion- Corrupted MR images Using AI Generated Contrast.

Jinghang Li, Tales Santini, Courtney Clark, Bruno Almeida, Cong Chu, Salem Alkhateeb, Andrea Sajewski, Jacob Berardinelli, Hecheng Jin, Tobias Campos and 6 more

Abstract readPreprint
In one paragraph

Article in Research square, 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

16 authors.

Jinghang LiUniversity of Pittsburgh.
Tales SantiniUniversity of Pittsburgh.
Courtney ClarkUniversity of Pittsburgh.
Bruno AlmeidaUniversity of Pittsburgh.
Cong ChuUniversity of Pittsburgh.
Salem AlkhateebUniversity of Pittsburgh.
Andrea SajewskiUniversity of Pittsburgh.
Jacob BerardinelliUniversity of Pittsburgh.
Hecheng JinUniversity of Pittsburgh.
Tobias CamposUniversity of Pittsburgh.
Jeremy J BerardoUniversity of Pittsburgh.
Joseph MettenburgUniversity of Pittsburgh Medical Center.
Ariel GildengersUniversity of Pittsburgh Medical Center.
Howard J AizensteinUniversity of Pittsburgh Medical Center.
Minjie WuUniversity of Pittsburgh Medical Center.
Tamer S IbrahimUniversity of Pittsburgh.

Funding

Evaluation of Brain and Cognitive Changes in Older Adults with MCI Taking Lithium to Prevent Alzheimer Type DementiaR01AG055389 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI GILDENGERS, ARIEL GERARD · 2017 to 2023
$5.4M
Imaging Advancements in Small Vessel and CSF Flow Pathophysiology of Pre-clinical Alzheimer's DiseaseR01AG063525 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI AIZENSTEIN, HOWARD J, COHEN, ANN D. · 2019 to 2023
$3.7M
High Performance Imaging for Assessment of Small Vessel Disease in Older Adults with DepressionR01MH111265 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI AIZENSTEIN, HOWARD J, IBRAHIM, TAMER S · 2016 to 2020
$3.6M
SARS-CoV-2 and Precursors of Alzheimer's Disease and Related Dementias: An Ultrahigh Field (7T) MRI Study in a Diverse Multinational CohortR56AG074467 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI GIRARD, TIMOTHY D, HOSSEINI, AKRAM A. · 2021 to 2021
$3.5M
7T Vascular and Molecular Imaging of SVD: Sex, Equol, and Risk of Alzheimer’s DiseaseR01AG085566 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HOWARD J AIZENSTEIN, AKIRA SEKIKAWA · 2024 to 2026
$2.1M
High-Throughput Computing for Genomics and Bioinformatics ResearchS10OD028483 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LEE, ADRIAN V · 2021 to 2021
$574k
NIA NIH HHS R01 AG055389NIA NIH HHS R01 AG063525NIA NIH HHS R01 AG085566NIA NIH HHS R56 AG074467NIH HHS S10 OD028483NIMH NIH HHS R01 MH111265
6 · The paper itself

Abstract

Hippocampal subfield segmentation requires high-resolution T2w turbo spin echo (TSE) MRI, yet this sequence is susceptible to motion artifacts, leading to substantial data loss. We developed a conditional generative model (

Indexed as

7T/3THippocampus subfield analysisMRI contrast synthesis

Identifiers

PMID42370237
PMCPMC13308394

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.