中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Atherosclerotic Plaque Pathological Analysis by Unsupervised K-Means Clustering.

文献类型:期刊论文

作者Zhang, Yongtao; Liu, Xin; Yue, Guanghua; Su, Haijun; Zhang, Peng-Fei; Feng, Jianqin
刊名IEEE ACCESS
出版日期2018
文献子类期刊论文
英文摘要This paper introduced a high-throughput pathological analysis algorithm by using of unsupervised K-means clustering principle and lab color space. The accuracy of this algorithm was verified by comparing with well-established commercially available software. For each type of pathological staining special for atherosclerotic plaque components analysis, accurate pathological analysis results could be obtained by selecting the appropriate cluster classification number (usually 3 to 5, but not limited to 3 to 5). Bland-Altman and linear regression analysis further confirmed that the self-developed algorithm correlated well with the well-established software (correlation coefficient R-2 ranged from 0.72 to 0.99). Moreover, the intra- and inter- observer coefficient of variation were relatively minor, indicating very good reproducibility. So we draw a conclusion that the self-developed algorithm could reduce the human interference factors, improve the efficiency, and be suitable for a large number of analyses of atherosclerotic pathology.
URL标识查看原文
语种英语
源URL[http://ir.siat.ac.cn:8080/handle/172644/14325]  
专题深圳先进技术研究院_医工所
推荐引用方式
GB/T 7714
Zhang, Yongtao,Liu, Xin,Yue, Guanghua,et al. Atherosclerotic Plaque Pathological Analysis by Unsupervised K-Means Clustering.[J]. IEEE ACCESS,2018.
APA Zhang, Yongtao,Liu, Xin,Yue, Guanghua,Su, Haijun,Zhang, Peng-Fei,&Feng, Jianqin.(2018).Atherosclerotic Plaque Pathological Analysis by Unsupervised K-Means Clustering..IEEE ACCESS.
MLA Zhang, Yongtao,et al."Atherosclerotic Plaque Pathological Analysis by Unsupervised K-Means Clustering.".IEEE ACCESS (2018).

入库方式: OAI收割

来源:深圳先进技术研究院

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