Open AccessMANTiS : a program for the analysis of X‐ray spectromicroscopy data
Author(s) -
Lerotic Mirna,
Mak Rachel,
Wirick Sue,
Meirer Florian,
Jacobsen Chris
Publication year - 2014
Publication title -
journal of synchrotron radiation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.172
H-Index - 99
ISSN - 1600-5775
DOI - 10.1107/s1600577514013964
Subject(s) - python (programming language) , computer science , principal component analysis , artificial intelligence , sample (material) , pattern recognition (psychology) , data mining , computer vision , computer graphics (images) , physics , operating system , thermodynamics
Spectromicroscopy combines spectral data with microscopy, where typical datasets consist of a stack of images taken across a range of energies over a microscopic region of the sample. Manual analysis of these complex datasets can be time‐consuming, and can miss the important traits in the data. With this in mind we have developed MANTiS , an open‐source tool developed in Python for spectromicroscopy data analysis. The backbone of the package involves principal component analysis and cluster analysis, classifying pixels according to spectral similarity. Our goal is to provide a data analysis tool which is comprehensive, yet intuitive and easy to use. MANTiS is designed to lead the user through the analysis using story boards that describe each step in detail so that both experienced users and beginners are able to analyze their own data independently. These capabilities are illustrated through analysis of hard X‐ray imaging of iron in Roman ceramics, and soft X‐ray imaging of a malaria‐infected red blood cell.