Projects per year
Abstract
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.
Original language | English |
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Article number | 20818 |
Journal | Scientific Reports |
Volume | 11 |
Issue number | 1 |
DOIs | |
Publication status | Published - 21 Oct 2021 |
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Dive into the research topics of 'Enhanced hyperspectral tomography for bioimaging by spatiospectral reconstruction'. Together they form a unique fingerprint.Projects
- 2 Finished
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Tomographic Imaging CCPi
Withers, P. (PI), Lee, P. (CoI) & Lionheart, W. (CoI)
29/08/15 → 28/08/20
Project: Research
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Next Generation Multi-Dimensional X-ray Imaging
Withers, P. (PI), Burke, G. (CoI), Cernik, R. (CoI), Haigh, S. (CoI), Lee, P. (CoI) & Lionheart, W. (CoI)
1/02/15 → 31/01/20
Project: Research