Application of Multivariate Statistical Analysis to Spectrum-Imaging Datasets: Benefits and Disadvantages

DOI Web Site

Bibliographic Information

Other Title
  • 多変量統計解析を利用したスペクトル・イメージの解析：利点と問題点
  • タヘンリョウ トウケイ カイセキ オ リヨウ シタ スペクトル ・ イメージ ノ カイセキ : リテン ト モンダイテン

Search this article

Abstract

<p>Multivariate statistical analysis (MSA) is one of essential approaches to effectively analyze large scale spectrum imaging (SI) datasets, which can be acquired in modern analytical electron microscopes (AEMs). In this article, first, principles and advantages of the MSA approaches based on the most popular principal component analysis (PCA) will be explained with several applications. Then, some issues/artifacts that might be introduced by applying the PCA method are also addressed. Finally, the recently developed LocalPCA method is also introduced，which has been developed by the authors to overcome some of artifacts introduced by the PCA.</p>

Journal

  • KENBIKYO

    KENBIKYO 50 (1), 23-27, 2015-04-30

    The Japanese Society of Microscopy

Keywords

Details 詳細情報について

Report a problem

Back to top