Evidence map›Paper›PMID 30840730›Full record

ArticleJournal of medical imaging (Bellingham, Wash.)2019

Development and evaluation of a method for segmentation of cardiac, subcutaneous, and visceral adipose tissue from Dixon magnetic resonance images.

Jon D Klingensmith, Addison L Elliott, Amy H Givan, Zechariah D Faszold, Cory L Mahan, Adam M Doedtman, Maria Fernandez-Del-Valle

Abstract read
In one paragraph

Article in Journal of medical imaging (Bellingham, Wash.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Precision or Paradox? AI-Driven Adiposity Imaging in Women With Overweight and Obesity: A Systematic Review and Meta-Analysis.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026
    Pooled it
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

7 authors.

Jon D KlingensmithSouthern Illinois University Edwardsville, Department of Electrical and Computer Engineering, Edwardsville, Illinois, United States.ORCID https://orcid.org/0000-0003-3770-2754
Addison L ElliottSouthern Illinois University Edwardsville, Department of Electrical and Computer Engineering, Edwardsville, Illinois, United States.
Amy H GivanSouthern Illinois University Edwardsville, Department of Applied Health, Edwardsville, Illinois, United States.
Zechariah D FaszoldSouthern Illinois University Edwardsville, Department of Electrical and Computer Engineering, Edwardsville, Illinois, United States.
Cory L MahanSouthern Illinois University Edwardsville, Department of Applied Health, Edwardsville, Illinois, United States.
Adam M DoedtmanSouthern Illinois University Edwardsville, Department of Applied Health, Edwardsville, Illinois, United States.
Maria Fernandez-Del-ValleSouthern Illinois University Edwardsville, Department of Applied Health, Edwardsville, Illinois, United States.

Funding

WU INSTITUTE OF CLINICAL AND TRANSLATIONAL SCIENCESUL1TR002345 · NCATS · WASHINGTON UNIVERSITY · PI William G. Powderly · 2017 to 2026
$97.8M
NCATS NIH HHS UL1 TR002345
6 · The paper itself

Abstract

Magnetic resonance imaging (MRI) has evolved into the gold standard for quantifying excess adiposity, but reliable, efficient use in longitudinal studies requires analysis of large numbers of images. The objective of this study is to develop and evaluate a segmentation method designed to identify cardiac, subcutaneous, and visceral adipose tissue (VAT) in Dixon MRI scans. The proposed method is evaluated using 10 scans from volunteer females 18- to 35-years old, with body mass indexes between 30 and

Indexed as

adipose tissueimage processingmagnetic resonance imagingobesitysegmentation

Identifiers

PMID30840730
PMCPMC6366476

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.