Automated Internal Classification of Beadless Chinese ZhuJi Freshwater Pearls based on Optical Coherence Tomography Images.

Yang Zhou, Tiebing Liu, Yang Shi, Zhengwei Chen, Jianwei Mao, Wujie Zhou

Erratum issuedAbstract read

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Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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.

Using optical coherence tomography to assess luster of pearls: technique suitability and insights.Scientific reports · 2024
Article

4 · The record

Corrections and comments

Erratum issued
Corrigendum: Automated Internal Classification of Beadless Chinese ZhuJi Freshwater Pearls based on Optical Coherence Tomography Images.2017

5 · Who and what money

Authors and funding

6 authors.

Yang ZhouSchool of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, 310023, China.

Tiebing LiuInstitute Zhejiang Provincial key Lab for Chem&Bio Processing Technology of Farm Product, Hangzhou, 310023, China.

Yang ShiSchool of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, 310023, China.

Zhengwei ChenCenter of Engineering Training, Zhejiang University of Science and Technology, Hangzhou, 310023, China.

Jianwei MaoInstitute Zhejiang Provincial key Lab for Chem&Bio Processing Technology of Farm Product, Hangzhou, 310023, China.

Wujie ZhouSchool of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, 310023, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optical coherence tomography (OCT) has been applied to inspect the internal defect of beadless Chinese ZhuJi fleshwater pearls. A novel fully automated algorithm is proposed to classify between normal and defective sub-layer in nacre layer. Our algorithm utilizes the graph segmentation approach to estimate the up and down boundaries of defect sub-layers from flattened and cropped image, and also proposes the strategy for edge and weight construction in segmentation process. The vertical gradients of boundary pixels are used to make grading decision. The algorithm is tested by typical pearl samples, and achieves 100% classification accuracy. The experiment result shows the feasibility and adaptability of the proposed approach, and proves that the OCT technique combined with proposed algorithm is a potential tool for fast and non-destructive diagnosis of internal structure of beadless pearl.

Identifiers

PMID27666087

DOI10.1038/srep33819

PMCPMC5036028

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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.