TY - GEN
T1 - Improving chemical mapping algorithm and visualization in full-field hard x-ray spectroscopic imaging
AU - Chang, Cheng
AU - Xu, Wei
AU - Chen-Wiegart, Yu Chen Karen
AU - Wang, Jun
AU - Yu, Dantong
PY - 2014
Y1 - 2014
N2 - X-ray Absorption Near Edge Structure (XANES) imaging, an advanced absorption spectroscopy technique, at the Transmission X-ray Microscopy (TXM) Beamline X8C of NSLS enables high-resolution chemical mapping (a.k.a. chemical composition identification or chemical spectra fitting). Two-Dimensional (2D) chemical mapping has been successfully applied to study many functional materials to decide the percentages of chemical components at each pixel position of the material images. In chemical mapping, the attenuation coefficient spectrum of the material (sample) can be fitted with the weighted sum of standard spectra of individual chemical compositions, where the weights are the percentages to be calculated. In this paper, we first implemented and compared two fitting approaches: (i) a brute force enumeration method, and (ii) a constrained least square minimization algorithm proposed by us. Next, as 2D spectra fitting can be conducted pixel by pixel, so theoretically, both methods can be implemented in parallel. In order to demonstrate the feasibility of parallel computing in the chemical mapping problem and investigate how much efficiency improvement can be achieved, we used the second approach as an example and implemented a parallel version for a multi-core computer cluster. Finally we used a novel way to visualize the calculated chemical compositions, by which domain scientists could grasp the percentage difference easily without looking into the real data.
AB - X-ray Absorption Near Edge Structure (XANES) imaging, an advanced absorption spectroscopy technique, at the Transmission X-ray Microscopy (TXM) Beamline X8C of NSLS enables high-resolution chemical mapping (a.k.a. chemical composition identification or chemical spectra fitting). Two-Dimensional (2D) chemical mapping has been successfully applied to study many functional materials to decide the percentages of chemical components at each pixel position of the material images. In chemical mapping, the attenuation coefficient spectrum of the material (sample) can be fitted with the weighted sum of standard spectra of individual chemical compositions, where the weights are the percentages to be calculated. In this paper, we first implemented and compared two fitting approaches: (i) a brute force enumeration method, and (ii) a constrained least square minimization algorithm proposed by us. Next, as 2D spectra fitting can be conducted pixel by pixel, so theoretically, both methods can be implemented in parallel. In order to demonstrate the feasibility of parallel computing in the chemical mapping problem and investigate how much efficiency improvement can be achieved, we used the second approach as an example and implemented a parallel version for a multi-core computer cluster. Finally we used a novel way to visualize the calculated chemical compositions, by which domain scientists could grasp the percentage difference easily without looking into the real data.
KW - Chemical mapping
KW - Parallel computing
KW - Spectra fitting
KW - Spectroscopy
KW - Visualization
KW - XANES
UR - https://www.scopus.com/pages/publications/84894570528
U2 - 10.1117/12.2041109
DO - 10.1117/12.2041109
M3 - Conference contribution
AN - SCOPUS:84894570528
SN - 9780819499349
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Proceedings of SPIE-IS and T Electronic Imaging - Visualization and Data Analysis 2014
T2 - 21st annual IS and T/SPIE Conference on Visualization and Analysis, VDA 2014
Y2 - 3 February 2014 through 5 February 2014
ER -