Image fusion of x-ray and electron tomograms

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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.
    Original languageEnglish
    Title of host publication2018 IEEE International Conference on Image Processing
    EditorsChristophoros Nikou, Kostas Plataniotis
    Place of PublicationPiscataway
    PublisherIEEE
    Number of pages5
    Publication statusPublished - 2018
    Event2018 IEEE International Conference on Image Processing - Athens, Greece
    Duration: 7 Oct 2018 → …

    Conference

    Conference2018 IEEE International Conference on Image Processing
    CountryGreece
    CityAthens
    Period7/10/18 → …

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