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Gewählte Publikation:

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Publikationstyp: Zeitschriftenaufsatz
Dokumenttyp: Originalarbeit

Jahr: 2021

AutorInnen: Warr, R; Ametova, E; Cernik, RJ; Fardell, G; Handschuh, S; Jørgensen, JS; Papoutsellis, E; Pasca, E; Withers, PJ

Titel: Enhanced hyperspectral tomography for bioimaging by spatiospectral reconstruction.

Quelle: Sci Rep. 2021; 11(1):20818

Autor/innen der Vetmeduni Vienna:

Handschuh Stephan

Beteiligte Vetmed-Organisationseinheiten

Here we apply hyperspectral bright field imaging to collect computed tomographic images with excellent energy resolution (~ 1 keV), applying it for the first time to map the distribution of stain in a fixed biological sample through its characteristic K-edge. Conventionally, because the photons detected at each pixel are distributed across as many as 200 energy channels, energy-selective images are characterised by low count-rates and poor signal-to-noise ratio. This means high X-ray exposures, long scan times and high doses are required to image unique spectral markers. Here, we achieve high quality energy-dispersive tomograms from low dose, noisy datasets using a dedicated iterative reconstruction algorithm. This exploits the spatial smoothness and inter-channel structural correlation in the spectral domain using two carefully chosen regularisation terms. For a multi-phase phantom, a reduction in scan time of 36 times is demonstrated. Spectral analysis methods including K-edge subtraction and absorption step-size fitting are evaluated for an ex vivo, single (iodine)-stained biological sample, where low chemical concentration and inhomogeneous distribution can affect soft tissue segmentation and visualisation. The reconstruction algorithms are available through the open-source Core Imaging Library. Taken together, these tools offer new capabilities for visualisation and elemental mapping, with promising applications for multiply-stained biological specimens.© 2021. The Author(s).

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