Related Experiment Video
Updated: Jan 20, 2026

Quantifying X-Ray Fluorescence Data Using MAPS
Published on: February 17, 2018
X-ray data reconstruction from incomplete data sampling
Kárel García Medina1,2, Ernesto Estevez Rams2, Reinhard B Neder1
1Lehrstuhl für Kristallographie und Strukturphysik, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany.
None:
For specific setups, a diffraction pattern can contain gaps or missing information. For example, that is the case when several detectors are used simultaneously, but a particular angular range is not covered between each detector. In this article, a procedure for the reconstruction of the missing signal is proposed. It is based on a modified Papoulis-Gerchberg algorithm that considers features of the diffraction pattern without loss of generality. The mathematical basis of the algorithm is presented, and several cases, simulated and experimental, are used to test the performance and robustness of the proposed solution.
Related Concept Videos
14:58Quantifying X-Ray Fluorescence Data Using MAPS
11:063D Printing of Preclinical X-ray Computed Tomographic Data Sets
09:37Extracting Metrics for Three-dimensional Root Systems: Volume and Surface Analysis from In-soil X-ray Computed Tomography Data
How Data are Classified: Numerical Data
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
How Data are Classified: Categorical Data
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
06:19Fixed Target Serial Data Collection at Diamond Light Source

