Image fusion of x-ray and electron tomograms
Y. Guo (TU Delft - ImPhys/Quantitative Imaging)
B. Rieger (TU Delft - ImPhys/Quantitative Imaging)
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Abstract
With electron tomography, we can reconstruct a threedimensional
(3D) volume of a specimen from a series of its two-dimensional (2D) projection images on the nanoscale. In a scanning transmission electron microscope (STEM), element-specific maps and mass-contrast projections can be simultaneously acquired from the X-ray spectrometer and electron detector. The X-ray tomogram has high chemical specificity but low signal-to-noise ratio (SNR), while the electron tomogram has poor compositional information but high
SNR. In this paper, we adopt and modify a regression-based image fusion algorithm to combine these two complementary modalities, so that the fused version would maintain both high chemical specificity and high SNR. We demonstrate that our method improves reconstruction quality on an experimental dataset of a core-shell nanoparticle. Specifically, it delivers tomograms with sharper edges and smoother fore- and background, and hence can enable easier and more accurate 3Dcharacterization of such nanostructures.