Evidence map›Paper›PMID 42028468›Full record

ArticleMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention2026

WASABI: A Metric for Evaluating Morphometric Plausibility of Synthetic Brain MRIs.

Bahram Jafrasteh, Wei Peng, Cheng Wan, Yimin Luo, Ehsan Adeli, Qingyu Zhao

Abstract read
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Article in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 2026. 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

6 authors.

Bahram JafrastehDepartment of Radiology, Weill Cornell Medicine, New York, NY, USA.
Wei PengDepartment of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
Cheng WanDepartment of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA.
Yimin LuoDepartment of Radiology, Weill Cornell Medicine, New York, NY, USA.
Ehsan AdeliDepartment of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
Qingyu ZhaoDepartment of Radiology, Weill Cornell Medicine, New York, NY, USA.

Funding

Neural mechanisms of gait disturbances as individualized digital biomarker trajectories in preclinical dementiaR01AG089169 · NIA · STANFORD UNIVERSITY · PI Ehsan Adeli · 2024 to 2026
$4.5M
Longitudinal Analysis of Diffusion Tensor Imaging to Discover Adolescent Alcohol Use EffectR00AA028840 · NIAAA · WEILL MEDICAL COLL OF CORNELL UNIV · PI Qingyu Zhao · 2024 to 2026
$747k
NIAAA NIH HHS R00 AA028840NIA NIH HHS R01 AG089169
6 · The paper itself

Abstract

Generative models enhance neuroimaging through data augmentation, quality improvement, and rare condition studies. Despite advances in realistic synthetic MRIs, evaluations focus on texture and perception, lacking sensitivity to crucial morphometric fidelity. This study proposes a new metric, called WASABI (Wasserstein-Based Anatomical Brain Index), to assess the morphometric plausibility of synthetic brain MRIs. WASABI leverages

Indexed as

Anatomical FidelityBrain MRI SynthesisGenerative ModelsWasserstein Distance

Identifiers

PMID42028468
PMCPMC13102318

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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.