Quantitative Atomic-Resolution Electron Microscopy
1. Introduction Sandra Van Aert 2. Statistical parameter estimation theory Sandra Van Aert 3. Efficient fitting algorithm Sandra Van Aert 4. Statistics-based atom counting Sandra Van Aert 5. Atom column detection Sandra Van Aert 6. Optimal experiment design for nanoparticle atom-counting from ADF STEM images Sandra Van Aert 7. Maximum a posteriori probability Sandra Van Aert 8. Discussion and conclusions Sandra Van Aert 9. Phase retrieval methods applied to coherent imaging Tatiana Latychevskaia
Undergraduates, graduates, academics and researchers in the field of Advances in Imaging and Electron Physics
Peter Hawkes obtained his M.A. and Ph.D (and later, Sc.D.) from the University of Cambridge, where he subsequently held Fellowships of Peterhouse and of Churchill College. From 1959 – 1975, he worked in the electron microscope section of the Cavendish Laboratory in Cambridge, after which he joined the CNRS Laboratory of Electron Optics in Toulouse, of which he was Director in 1987. He was Founder-President of the European Microscopy Society and is a Fellow of the Microscopy and Optical Societies of America. He is a member of the editorial boards of several microscopy journals and serial editor of Advances in Electron Optics.
- Contains contributions from leading authorities on the subject matter
- Informs and updates on the latest developments in the field of imaging and electron physics
- Provides practitioners interested in microscopy, optics, image processing, mathematical morphology, electromagnetic fields, electrons and ion emission with a valuable resource
Date de parution : 04-2021
Ouvrage de 294 p.
15.2x22.8 cm
Thèmes de Quantitative Atomic-Resolution Electron Microscopy :
Mots-clés :
Atom detectability; Atom detection; Detection theory; Electron microscope design; High-resolution (scanning) transmission electron microscopy (HR(S)TEM); High-resolution scanning transmission electron microscopy (HRSTEM); Image processing; Integrated contrast-to-noise ratio (ICNR); Maximum a posteriori (MAP) probability; Model selection; Model-based fitting; Nanoparticle atom counting; Quantitative electron microscopy; Statistical parameter estimation theory