Modeling Nanoscale Imaging in Electron Microscopy presents the recent advances that have been made using mathematical methods to resolve problems in microscopy. With improvements in hardware-based aberration software significantly expanding the nanoscale imaging capabilities of scanning transmission electron microscopes (STEM), these mathematical models can replace some labor intensive procedures used to operate and maintain STEMs. This book, the first in its field since 1998, will also cover such relevant concepts as superresolution techniques, special denoising methods, application of mathematical/statistical learning theory, and compressed sensing.
Cuprins
Statistical and Information-Theoretic Analysis of Resolution in Imaging.- (Scanning) Transmission Electron Microscopy: Overview and Examples for the Non-Microscopist.- Seeing Atoms in the Crossroads of Microscopy and Mathematics.- Kantianism at the Nanoscale.- Reference free cryo-EM algorithms using self-consistent data fusion.- Reference free cryo-EM algorithms using self-consistent data fusion.- Applications of multivariate statistical analysis for large-scale spectrum-image datasets and atomic-resolution images.- Compressed Sensing.- Imaging the behavior of atoms, clusters and nanoparticles during elevated temperature experiments in an aberration-corrected electron microscope.- Towards Quantitative Imaging using Aberration Correction and Exit Wave Reconstruction.- Image registration, classification and averaging in cryo-electron tomography.- (Scanning) Transmission Electron Microscopy with High spatial, temporal and energy resolution.- Fluctuation Microscopy: Nanoscale Order in Amorphous Materials from Electron Nanodiffraction.- Information in super-resolution microscopy and automated analysis of large-scale calcium imaging data.- Concluding remarks on Imaging in Electron Microscopy.
Despre autor
Thomas Vogt is Director of the Nano Center Educational Foundation and Distinguished Professor of Chemistry & Biochemistry at the University of South Carolina.
Wolfgang Dahmen is a professor at RWTH Aachen.
Peter G. Binev is a Professor of Mathematics at the University of South Carolina.
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