We are happy to announce that Leopold Veselka, PhD student in the Sub-project Quantitative Coupled Physics Imaging, has successfully defended his PhD thesis with the title “Reconstruction of optical parameters in quantitative optical coherence tomography” on 9th of January, 2024.
Leopold’s doctoral study was supervised by Peter Elbau, the principal investigator of the Sub-project Quantitative Coupled Physics Imaging affiliated with the Faculaty of Mathematics, University of Vienna. Congratulations from the SFB colleagues!
On May 20, 2022 Ekaterina Sherina, Simon Hubmer, and Axel Kittenberger presented the SFB Tomography Across the Scales at the Austrian Science Festival: “Lange Nacht der Forschung“. To make tomography tangible we showcased our “optical DIY tomograph” described in Computed Origami Tomography.
The workshop is organized within this SFB research program and is centered around the mathematical and experimental problems related to the applications studied in this project, involving adaptive optics, optical coherence tomography, photoacoustics, and superresolution imaging.
On the 16th of July 2019 SFB coordinator Otmar Scherzer explained in the widely read newspaper “Kronenzeitung” within the weekly column “Krone der Wissensschaft” the general principles of tomography and in of particular photoacoustic tomography. The article is available in print only, but can be acquired here.
at Banff, Alberta from Sunday, June 23 to Friday June 28, 2019
Elena Beretta (NYU Abu Dhabi & Politecnico di Milano)
Uri Ascher (University of British Columbia)
Otmar Scherzer (University of Vienna)
Luminita Vese (University of California, Los Angeles)
Inverse problems require to determine the cause from a set of indirect observations.
Such problems appear in medical imaging, non destructive testing of materials, computerized tomography,
source reconstructions in acoustics, computer vision and geophysics, to mention but a few.
The 21st century is the golden age of computer imaging: Measurement devices have become
enormously powerful and huge amounts of data are recorded at every eye glimpse. Moreover,
computer technology has developed to such a high degree of efficiency that the evaluation of such
an enormous amount of data has become possible *if* adequate mathematical and
computational tools are used.
Recently, the community has been exposed to fundamentally new mathematical models (such as learning), which
stimulated exciting theoretical developments and new computational algorithms for solving complicated large
scale inverse problems. This workshop will survey modern and identify new mathematical and computational
developments for tackling such problems.
The Eurasian Association on Inverse Problems (EAIP) is a non-governmental organization working to ensure a coordination between inverse problems research groups and scientific schools in Eurasian countries, by providing international conferences, meetings and summer schools on inverse problems, both in theory and applications.
The association has established an “EAIP Award” to recognize outstanding scientific contributions to the field of inverse problems and continuous efforts to foster cooperation between researchers of Eurasian countries.