Scalable 3D Reconstruction From Single Particle X-Ray Diffraction Images Based on Online Machine Learning

• URL: http://arxiv.org/abs/2312.14432v1
• Date: Fri, 22 Dec 2023 04:41:31 GMT
• Title: Scalable 3D Reconstruction From Single Particle X-Ray Diffraction Images Based on Online Machine Learning
• Authors: Jay Shenoy, Axel Levy, Fr\'ed\'eric Poitevin, Gordon Wetzstein
• Abstract summary: We introduce X-RAI, an online reconstruction framework that estimates the structure of a 3D macromolecule from large X-ray SPI datasets. We demonstrate that X-RAI achieves state-of-the-art performance for small-scale datasets in simulation and challenging experimental settings.
• Score: 34.12502156343611
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: X-ray free-electron lasers (XFELs) offer unique capabilities for measuring the structure and dynamics of biomolecules, helping us understand the basic building blocks of life. Notably, high-repetition-rate XFELs enable single particle imaging (X-ray SPI) where individual, weakly scattering biomolecules are imaged under near-physiological conditions with the opportunity to access fleeting states that cannot be captured in cryogenic or crystallized conditions. Existing X-ray SPI reconstruction algorithms, which estimate the unknown orientation of a particle in each captured image as well as its shared 3D structure, are inadequate in handling the massive datasets generated by these emerging XFELs. Here, we introduce X-RAI, an online reconstruction framework that estimates the structure of a 3D macromolecule from large X-ray SPI datasets. X-RAI consists of a convolutional encoder, which amortizes pose estimation over large datasets, as well as a physics-based decoder, which employs an implicit neural representation to enable high-quality 3D reconstruction in an end-to-end, self-supervised manner. We demonstrate that X-RAI achieves state-of-the-art performance for small-scale datasets in simulation and challenging experimental settings and demonstrate its unprecedented ability to process large datasets containing millions of diffraction images in an online fashion. These abilities signify a paradigm shift in X-ray SPI towards real-time capture and reconstruction.

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