Evidence map›Paper›PMID 24803950›Full record

ArticleComputational and mathematical methods in medicine2014

A nonparametric shape prior constrained active contour model for segmentation of coronaries in CTA images.

Yin Wang, Han Jiang

Abstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

2 authors.

Yin WangState Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China ; College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
Han JiangState Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present a nonparametric shape constrained algorithm for segmentation of coronary arteries in computed tomography images within the framework of active contours. An adaptive scale selection scheme, based on the global histogram information of the image data, is employed to determine the appropriate window size for each point on the active contour, which improves the performance of the active contour model in the low contrast local image regions. The possible leakage, which cannot be identified by using intensity features alone, is reduced through the application of the proposed shape constraint, where the shape of circular sampled intensity profile is used to evaluate the likelihood of current segmentation being considered vascular structures. Experiments on both synthetic and clinical datasets have demonstrated the efficiency and robustness of the proposed method. The results on clinical datasets have shown that the proposed approach is capable of extracting more detailed coronary vessels with subvoxel accuracy.

Indexed as

AlgorithmsCoronary VesselsFalse Positive ReactionsHumansImage Processing, Computer-AssistedImaging, Three-DimensionalModels, StatisticalNormal DistributionRadiographic Image Interpretation, Computer-AssistedReproducibility of ResultsSoftwareTomography, X-Ray Computed

Identifiers

PMID24803950
PMCPMC3988742

What OpenQuestion holds

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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.