|About this Abstract
||2019 TMS Annual Meeting & Exhibition
||Characterization of Materials through High Resolution Imaging
||A Fast Algorithm for Improving Reconstruction Quality with Incomplete Tomography Data
||Xianghui Xiao, Ronald Agyei, Michael Sangid
|On-Site Speaker (Planned)
Tomography measurements usually require taking projection images of a sample in angle ranges of 180 or 360 degrees. In in situ tomography applications, it is sometime impossible to acquire complete data due to in situ sample environment control constraints. The missing data in tomography data can cause severe artifacts. We developed an algorithm based on interpolation to compensate for the missing data. The processed data can then be reconstructed with filtered-back-projection (FBP) type algorithms. This method is fast and efficient compared to iterative algorithms. In this talk, we will compare the performances of new algorithm and standard FBP and simultaneous iterative reconstruction technique (SIRT). The results shows the new algorithm can improve the reconstruction quality compared to the standard FBP while the reconstruction speed maintains superior to iterative algorithms.
||Planned: Supplemental Proceedings volume