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X-ray tomographic reconstruction and segmentation pipeline for the long-wavelength macromolecular crystallography beamline at Diamond Light Source

DOI: 10.1107/S1600577521003453 DOI Help

Authors: Daniil Kazantsev (University of Manchester) , Ramona Duman (Diamond Light Source) , Armin Wagner (Diamond Light Source) , Vitaliy Mykhaylyk (Diamond Light Source) , Kazimir Wanelik (Diamond Light Source) , Mark Basham (Diamond Light Source; Rosalind Franklin Institute) , Nicola Wadeson (Diamond Light Source)
Co-authored by industrial partner: No

Type: Journal Paper
Journal: Journal Of Synchrotron Radiation , VOL 28

State: Published (Approved)
Published: May 2021

Open Access Open Access

Abstract: In this paper a practical solution for the reconstruction and segmentation of low-contrast X-ray tomographic data of protein crystals from the long-wavelength macromolecular crystallography beamline I23 at Diamond Light Source is provided. The resulting segmented data will provide the path lengths through both diffracting and non-diffracting materials as basis for analytical absorption corrections for X-ray diffraction data taken in the same sample environment ahead of the tomography experiment. X-ray tomography data from protein crystals can be difficult to analyse due to very low or absent contrast between the different materials: the crystal, the sample holder and the surrounding mother liquor. The proposed data processing pipeline consists of two major sequential operations: model-based iterative reconstruction to improve contrast and minimize the influence of noise and artefacts, followed by segmentation. The segmentation aims to partition the reconstructed data into four phases: the crystal, mother liquor, loop and vacuum. In this study three different semi-automated segmentation methods are experimented with by using Gaussian mixture models, geodesic distance thresholding and a novel morphological method, RegionGrow, implemented specifically for the task. The complete reconstruction-segmentation pipeline is integrated into the MPI-based data analysis and reconstruction framework Savu, which is used to reduce computation time through parallelization across a computing cluster and makes the developed methods easily accessible.

Journal Keywords: long-wavelength X-ray crystallography; absorption correction; segmentation; iterative reconstruction; high-performance computing

Subject Areas: Information and Communication Technology

Instruments: I23-Long wavelength MX


Discipline Tags:

Information & Communication Technologies Data processing

Technical Tags:

Diffraction Imaging Macromolecular Crystallography (MX) Tomography