Evidence map›Paper›PMID 41503368›Full record

ArticleJournal of medical imaging (Bellingham, Wash.)2026

Synthetic multi-inversion time magnetic resonance images for visualization of subcortical structures.

Savannah P Hays, Lianrui Zuo, Anqi Feng, Yihao Liu, Blake E Dewey, Jiachen Zhuo, Ellen M Mowry, Scott D Newsome, Jerry L Prince, Aaron Carass

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of medical imaging (Bellingham, Wash.), 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

10 authors.

Savannah P HaysJohns Hopkins University, Image Analysis and Communications Laboratory, Department of Electrical and Computer Engineering, Baltimore, Maryland, United States.ORCID https://orcid.org/0009-0005-8711-1356
Lianrui ZuoVanderbilt University, Department of Electrical and Computer Engineering, Nashville, Tennessee, United States.ORCID https://orcid.org/0000-0002-5923-9097
Anqi FengJohns Hopkins University, Image Analysis and Communications Laboratory, Department of Electrical and Computer Engineering, Baltimore, Maryland, United States.
Yihao LiuVanderbilt University, Department of Electrical and Computer Engineering, Nashville, Tennessee, United States.ORCID https://orcid.org/0000-0003-3187-9903
Blake E DeweyJohns Hopkins University, Department of Neurology, Baltimore, Maryland, United States.ORCID https://orcid.org/0000-0003-4554-5058
Jiachen ZhuoUniversity of Maryland School of Medicine, Department of Diagnostic Radiology and Nuclear Medicine, Baltimore, Maryland, United States.
Ellen M MowryJohns Hopkins University, Department of Neurology, Baltimore, Maryland, United States.
Scott D NewsomeJohns Hopkins University, Department of Neurology, Baltimore, Maryland, United States.
Jerry L PrinceJohns Hopkins University, Image Analysis and Communications Laboratory, Department of Electrical and Computer Engineering, Baltimore, Maryland, United States.ORCID https://orcid.org/0000-0002-6553-0876
Aaron CarassJohns Hopkins University, Image Analysis and Communications Laboratory, Department of Electrical and Computer Engineering, Baltimore, Maryland, United States.ORCID https://orcid.org/0000-0003-4939-5085

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Visualization of subcortical gray matter is essential in neuroscience and clinical practice, particularly for disease understanding and surgical planning. Although multi-inversion time (multi-TI) Approach: We present SyMTIC (synthetic multi-TI contrasts), a deep learning method that generates synthetic multi-TI images using routinely acquired Results: SyMTIC was trained using paired magnetization prepared rapid acquisition with gradient echo (MPRAGE) and fast gray matter acquisition T1 inversion recovery (FGATIR) images along with Conclusion: SyMTIC enables robust generation of high-quality multi-TI images from routine MR contrasts. When paired with the HACA3 algorithm, it generalizes well to varied clinical datasets, including those without FLAIR or

Indexed as

brainimage synthesismagnetic resonance imaging

Identifiers

PMID41503368
PMCPMC12770912

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.