Application of signal separation to diffraction image compression and serial crystallography

TL;DR

This paper introduces a real-time diffraction image analysis method using a novel signal separation algorithm, enabling efficient data compression and peak detection in serial crystallography at high frame rates.

Contribution

The work presents a new signal separation algorithm tailored for azimuthal space, applied to diffraction image compression and peak-picking in serial crystallography.

Findings

Effective separation of amorphous and crystal diffraction signals.

Comparable data quality after compression with existing tools.

Enhanced peak detection performance in high-speed diffraction data.

Abstract

We present here a real-time analysis of diffraction images acquired at high frame-rate (925 Hz) and its application to macromolecular serial crystallography. The software uses a new signal separation algorithm, able to distinguish the amorphous (or powder diffraction) component from the diffraction signal originating from single crystals. It relies on the ability to work efficiently in azimuthal space and derives from the work performed on pyFAI, the fast azimuthal integration library. Two applications are built upon this separation algorithm: a lossy compression algorithm and a peak-picking algorithm; the performances of both is assessed by comparing data quality after reduction with XDS and CrystFEL.