Mathematical and Statistical Analysis of Spatial Data

Beskrivelse

Faster Imaging of Nanoscale Surfaces It is important in many areas of science to be able to measure details at nanoscale or, in principle as small scale as possible. The application areas range over the medical, biological, materials science areas etc. Examples could be investigating the surface structure of some catalyst material or investigating the shape and other surface properties of biological cells. The wavelengths of visible light pose natural restrictions on how small features can be resolved in optical microscopy and therefore other techniques have been developed. Some of these techniques, such as scanning electron microscopy and atomic force microscopy, allow imaging down to individual atoms in some cases. In our work, we focus on atomic force microscopy. The speed at which an atomic force microscope can image is limited by the fact that the microscope must sense the surface of the specimen by moving a tiny mechanical probe around the surface, measuring the surface at one discrete point at a time. In order to image a surface region, this is typically done in a dense raster pattern - a relatively slow procedure depending on the size of the region of interest and the desired resolution. In order to improve the image acquisition speed, we investigate the use of advanced image processing algorithms to reconstruct an image of the surface from fewer (less dense) measurements. Here we review and discuss some of the challenges and possible approaches to image reconstruction in atomic force microscopy and demonstrate some of our recent results.

Periode	1 jun. 2015
Begivenhedstitel	Mathematical and Statistical Analysis of Spatial Data
Begivenhedstype	Workshop
Placering	Aalborg, DanmarkVis på kort