Application of signal separation to diffraction image compression and serial crystallography
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arXiv
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| Auteurs principaux: | , , , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866917837685129216 |
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| author | Kieffer, Jérôme Orlans, Julien Coquelle, Nicolas Debionne, Samuel Basu, Shibom Homs, Alejandro Santonia, Gianluca De Sanctis, Daniele |
| author_facet | Kieffer, Jérôme Orlans, Julien Coquelle, Nicolas Debionne, Samuel Basu, Shibom Homs, Alejandro Santonia, Gianluca De Sanctis, Daniele |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_09515 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Application of signal separation to diffraction image compression and serial crystallography Kieffer, Jérôme Orlans, Julien Coquelle, Nicolas Debionne, Samuel Basu, Shibom Homs, Alejandro Santonia, Gianluca De Sanctis, Daniele Materials Science Image and Video Processing Optics 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. |
| title | Application of signal separation to diffraction image compression and serial crystallography |
| topic | Materials Science Image and Video Processing Optics |
| url | https://arxiv.org/abs/2411.09515 |