Evidence map›Paper›PMID 26689551›Full record

ArticlePloS one2015

Variational Reconstruction of Left Cardiac Structure from CMR Images.

Min Wan, Wei Huang, Jun-Mei Zhang, Xiaodan Zhao, Ru San Tan, Xiaofeng Wan, Liang Zhong

Abstract read
In one paragraph

Article in PloS one, 2015. 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

7 authors.

Min WanNanchang University, Nanchang, Jiangxi Province, P.R.China 330031.
Wei HuangNanchang University, Nanchang, Jiangxi Province, P.R.China 330031.
Jun-Mei ZhangNational Heart Centre Singapore, 5 Hospital Drive, Singapore 169609, Singapore.
Xiaodan ZhaoNational Heart Centre Singapore, 5 Hospital Drive, Singapore 169609, Singapore.
Ru San TanNational Heart Centre Singapore, 5 Hospital Drive, Singapore 169609, Singapore.
Xiaofeng WanNanchang University, Nanchang, Jiangxi Province, P.R.China 330031.
Liang ZhongNational Heart Centre Singapore, 5 Hospital Drive, Singapore 169609, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiovascular Disease (CVD), accounting for 17% of overall deaths in the USA, is the leading cause of death over the world. Advances in medical imaging techniques make the quantitative assessment of both the anatomy and function of heart possible. The cardiac modeling is an invariable prerequisite for quantitative analysis. In this study, a novel method is proposed to reconstruct the left cardiac structure from multi-planed cardiac magnetic resonance (CMR) images and contours. Routine CMR examination was performed to acquire both long axis and short axis images. Trained technologists delineated the endocardial contours. Multiple sets of two dimensional contours were projected into the three dimensional patient-based coordinate system and registered to each other. The union of the registered point sets was applied a variational surface reconstruction algorithm based on Delaunay triangulation and graph-cuts. The resulting triangulated surfaces were further post-processed. Quantitative evaluation on our method was performed via computing the overlapping ratio between the reconstructed model and the manually delineated long axis contours, which validates our method. We envisage that this method could be used by radiographers and cardiologists to diagnose and assess cardiac function in patients with diverse heart diseases.

Indexed as

AlgorithmsHeartHumansImage Interpretation, Computer-AssistedMagnetic Resonance Imaging, CineModels, Cardiovascular

Identifiers

PMID26689551
PMCPMC4699201

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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.