Date of Award
Spring 3-20-2023
Degree Name
Bachelor of Arts (A.B.)
Restricted/Unrestricted
Unrestricted
Abstract
Modern sample imaging techniques produce data in the form of large mosaics, wherein every pixel contains valuable mineralogical information. These heavy data files are challenging for most computers to load and process, furthermore access to lunar and other extraterrestrial samples is limited. We developed the QME Tool to display optical, electron, and quantitative x-ray maps in conjunction with one another to overcome these challenges and advance mineralogy data presentation and analysis. The images and quantitative data was collected using specialized techniques, followed by an extensive image co-registration process. The interface was developed using OpenSeadragon, “An open-source, web-based viewer for high-resolution zoomable images, implemented in pure JavaScript, for desktop and mobile”[1], and the files were processed using Geotiff.js, a JavaScript “library to parse TIFF files for visualization or analysis”[2]. We created three methods of data extraction: single-pixel selection, rectangular region selection, and polygonal region selection. Each of the three methods allows the user to retrieve quantitative data in the form of weight percentages of 10 common oxide compounds. The QME tool is the next-gen integration of compositional data with rapid online visualization, optimized to suit the needs for future lunar sample imaging.
Mentor
Ryan Ogliore
Additional Advisors
Brad L. Jolliff
Recommended Citation
Minocha, Angelina, "The Quantitative Microanalysis Explorer: Introducing web-based visualization for optical, electron, and quantitative x-ray maps for studying lunar samples" (2023). Senior Honors Papers / Undergraduate Theses. 57.
https://openscholarship.wustl.edu/undergrad_etd/57