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Upscaling X‐ray nanoimaging to macroscopic specimens
Author(s) -
Du Ming,
Di Zichao Wendy,
Gürsoy Dogˇa,
Xian R. Patrick,
Kozorovitskiy Yevgenia,
Jacobsen Chris
Publication year - 2021
Publication title -
journal of applied crystallography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.429
H-Index - 162
ISSN - 1600-5767
DOI - 10.1107/s1600576721000194
Subject(s) - connectomics , connectome , computer science , microscopy , detector , optics , frame rate , physics , artificial intelligence , neuroscience , biology , functional connectivity
Upscaling X‐ray nanoimaging to macroscopic specimens has the potential for providing insights across multiple length scales, but its feasibility has long been an open question. By combining the imaging requirements and existing proof‐of‐principle examples in large‐specimen preparation, data acquisition and reconstruction algorithms, the authors provide imaging time estimates for howX‐ray nanoimaging can be scaled to macroscopic specimens. To arrive at this estimate, a phase contrast imaging model that includes plural scattering effects is used to calculate the required exposure and corresponding radiation dose. The coherent X‐ray flux anticipated from upcoming diffraction‐limited light sources is then considered. This imaging time estimation is in particular applied to the case of the connectomes of whole mouse brains. To image the connectome of the whole mouse brain, electron microscopy connectomics might require years, whereas optimized X‐ray microscopy connectomics could reduce this to one week. Furthermore, this analysis points to challenges that need to be overcome (such as increased X‐ray detector frame rate) and opportunities that advances in artificial‐intelligence‐based `smart' scanning might provide. While the technical advances required are daunting, it is shown that X‐ray microscopy is indeed potentially applicable to nanoimaging of millimetre‐ or even centimetre‐size specimens.