Evidence map›Paper›PMID 28438178›Full record

ArticleBiomedical engineering online2017

Automatic construction of statistical shape models using deformable simplex meshes with vector field convolution energy.

Jinke Wang, Changfa Shi

Abstract readEvaluation Study
In one paragraph

Article in Biomedical engineering online, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Review
  3. Statistical shape model of the talus bone morphology: A comparison between impinged and nonimpinged ankles.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2023
    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.

Jinke WangDepartment of Software Engineering, Harbin University of Science and Technology, Rongcheng, 264300, China.ORCID http://orcid.org/0000-0002-1755-4734
Changfa ShiMobile E-business Collaborative Innovation Center of Hunan Province, Hunan University of Commerce, Changsha, 410205, China. ivanhanks@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the active shape model framework, principal component analysis (PCA) based statistical shape models (SSMs) are widely employed to incorporate high-level a priori shape knowledge of the structure to be segmented to achieve robustness. A crucial component of building SSMs is to establish shape correspondence between all training shapes, which is a very challenging task, especially in three dimensions.

methodsWe propose a novel mesh-to-volume registration based shape correspondence establishment method to improve the accuracy and reduce the computational cost. Specifically, we present a greedy algorithm based deformable simplex mesh that uses vector field convolution as the external energy. Furthermore, we develop an automatic shape initialization method by using a Gaussian mixture model based registration algorithm, to derive an initial shape that has high overlap with the object of interest, such that the deformable models can then evolve more locally. We apply the proposed deformable surface model to the application of femur statistical shape model construction to illustrate its accuracy and efficiency.

resultsExtensive experiments on ten femur CT scans show that the quality of the constructed femur shape models via the proposed method is much better than that of the classical spherical harmonics (SPHARM) method. Moreover, the proposed method achieves much higher computational efficiency than the SPHARM method.

conclusionsThe experimental results suggest that our method can be employed for effective statistical shape model construction.

Indexed as

AlgorithmsModels, StatisticalAdultAgedComputer SimulationFemaleFemurHumansImage EnhancementImaging, Three-DimensionalMaleMiddle AgedModels, AnatomicModels, BiologicalPattern Recognition, AutomatedRadiographic Image Interpretation, Computer-AssistedDeformable modelsGreedy algorithmShape correspondence establishmentShape model constructionSimplex meshesVFC energy

Identifiers

PMID28438178
PMCPMC5404340

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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.