中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Information Entropy-Based Strategy for the Quantitative Evaluation of Extensive Hyperspectral Images to Better Unveil Spatial Heterogeneity in Mass Spectrometry Imaging

文献类型:期刊论文

作者Wu, Wenyong5,6; Hou, Jinjun5; Zhang, Zijia4,5; Li, Feifei4,5; Zhang, Rong4,5; Gao, Lei4,5; Ni, Hui5,6; Zhang, Tengqian4,5; Long, Huali5; Lei, Min4,5
刊名ANALYTICAL CHEMISTRY
出版日期2022-07-26
卷号94期号:29页码:10355-10366
ISSN号0003-2700
DOI10.1021/acs.analchem.2c00370
通讯作者Huang, Ruimin(rmhuang@simm.ac.cn) ; Zeng, Zhongda(adawin.tsang@qq.com) ; Wu, Wanying(wanyingwu@simm.ac.cn)
英文摘要Hyperspectral images can be generated from mass spectrometry imaging (MSI) data for the intuitive data visualization purpose. However, hundreds of HSIs can be generated by different dimensionality reduction methods, which poses great challenges in selecting the high-quality images with the best intuitive visualization results of the MSI data. Here, we presented a novel approach that objectively evaluates the image quality of the hyperspectral images. The applicability of this method was demonstrated by analyzing the MSI data acquired from human prostate cancer biopsy samples and mouse brain tissue section, which harbored an intrinsic tissue heterogeneity. Our method was based on the information entropy and contrast measured from image information content and image definition, respectively. The heterogeneity of the MSI data from high-dimensional space was reduced to three-dimensional embeddings and thoroughly evaluated to achieve satisfactory visualization results. The application of information entropy and contrast can be used to choose the optimized visualization results rapidly and objectively from an extensive number of hyperspectral images and be adopted to evaluate and optimize different dimensionality reduction algorithms and their hyperparameter combinations. In conclusion, the information entropy-based strategy could be a bridge between chemometrician and biologists.
WOS关键词QUALITY ASSESSMENT
资助项目National Natural Sciences Foundation of China[81973455]
WOS研究方向Chemistry
语种英语
出版者AMER CHEMICAL SOC
WOS记录号WOS:000829345000001
源URL[http://119.78.100.183/handle/2S10ELR8/302031]  
专题中国科学院上海药物研究所
通讯作者Huang, Ruimin; Zeng, Zhongda; Wu, Wanying
作者单位1.Dalian Univ, Coll Environm & Chem Engn, Dalian 116622, Peoples R China
2.Fudan Univ, Dept Lab Anim Sci, Shanghai 200032, Peoples R China
3.Shanghai Jiao Tong Univ, Shanghai Gen Hosp, Sch Med, Dept Urol, Shanghai 200080, Peoples R China
4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
5.Chinese Acad Sci, Natl Engn Res Ctr TCM Standardizat Technol, Shanghai Inst Mat Med, Shanghai 201203, Peoples R China
6.Nanjing Univ Chinese Med, Sch Chinese Mat Med, Nanjing 210029, Peoples R China
推荐引用方式
GB/T 7714
Wu, Wenyong,Hou, Jinjun,Zhang, Zijia,et al. Information Entropy-Based Strategy for the Quantitative Evaluation of Extensive Hyperspectral Images to Better Unveil Spatial Heterogeneity in Mass Spectrometry Imaging[J]. ANALYTICAL CHEMISTRY,2022,94(29):10355-10366.
APA Wu, Wenyong.,Hou, Jinjun.,Zhang, Zijia.,Li, Feifei.,Zhang, Rong.,...&Wu, Wanying.(2022).Information Entropy-Based Strategy for the Quantitative Evaluation of Extensive Hyperspectral Images to Better Unveil Spatial Heterogeneity in Mass Spectrometry Imaging.ANALYTICAL CHEMISTRY,94(29),10355-10366.
MLA Wu, Wenyong,et al."Information Entropy-Based Strategy for the Quantitative Evaluation of Extensive Hyperspectral Images to Better Unveil Spatial Heterogeneity in Mass Spectrometry Imaging".ANALYTICAL CHEMISTRY 94.29(2022):10355-10366.

入库方式: OAI收割

来源:上海药物研究所

浏览0
下载0
收藏0
其他版本

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。