Lerotic Mirna, Mak Rachel, Wirick Sue, Meirer Florian, Jacobsen Chris
2nd Look Consulting, Room 1702, 17/F, Tung Hip Commercial Building, 248 Des Voeux Road, Hong Kong.
Department of Physics and Astronomy, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208-3112, USA.
J Synchrotron Radiat. 2014 Sep;21(Pt 5):1206-12. doi: 10.1107/S1600577514013964. Epub 2014 Jul 31.
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.
光谱显微镜技术将光谱数据与显微镜技术相结合,典型的数据集由在样品微观区域内一系列能量下拍摄的一叠图像组成。对这些复杂数据集进行人工分析可能非常耗时,并且可能会遗漏数据中的重要特征。考虑到这一点,我们开发了MANTiS,这是一个用Python开发的用于光谱显微镜数据分析的开源工具。该软件包的核心涉及主成分分析和聚类分析,根据光谱相似性对像素进行分类。我们的目标是提供一个全面、直观且易于使用的数据分析工具。MANTiS旨在通过详细描述每个步骤的故事板引导用户进行分析,以便有经验的用户和初学者都能够独立分析自己的数据。通过对罗马陶瓷中铁的硬X射线成像以及疟疾感染红细胞的软X射线成像分析,展示了这些功能。