Undersampling Raster Scans in Spectromicroscopy for reduced dose and faster measurements

TL;DR

This paper introduces a novel undersampling approach using low-rank matrix completion to significantly reduce dose and scanning time in X-ray spectromicroscopy, enabling faster measurements with less material degradation.

Contribution

The paper presents a new undersampling technique that skips raster rows and reconstructs data, reducing sampling by 5-6 times in spectromicroscopy.

Findings

Achieved 5-6x reduction in sampling

Robust reconstruction of spectromicroscopic data

Reduced dose and faster measurement times

Abstract

Combinations of spectroscopic analysis and microscopic techniques are used across many disciplines of scientific research, including material science, chemistry and biology. X-ray spectromicroscopy, in particular, is a powerful tool used for studying chemical state distributions at the micro and nano scales. With the beam fixed, a specimen is typically rastered through the probe with continuous motion and a range of multimodal data is collected at fixed time intervals. The application of this technique is limited in some areas due to: long scanning times to collect the data, either because of the area/volume under study or the compositional properties of the specimen; and material degradation due to the dose absorbed during the measurement. In this work, we propose a novel approach for reducing the dose and scanning times by undersampling the raster data. This is achieved by skipping rows within scans and reconstructing the x-ray spectromicroscopic measurements using low-rank matrix completion. The new method is robust and allows for x 5-6 reduction in sampling. Experimental results obtained on real data are illustrated.