M21. Imaging Modalities: Recent Advances and Beyond

The past century has witnessed accelerated development in imaging techniques for medical, biological, industrial and geophysical applications using a wide range of physical modalities. Examples include microscopy, ultrasound, X-ray transmission, positron emission, magnetic resonance, electrical impedance, photoacoustic effect, microwave radiation, atmospheric muons, and seismic waves. The realm of imaging modalities is constantly expanding. Because of their non-intrusive nature, each image reconstruction technique requires finding the solution of an ill-posed mathematical inverse problem to recover the physical properties of a medium using only external measurements. However, each modality and application considered still provides different challenges from both the theoretical and computational point of views. This mini-symposium is aiming to highlight some of the most recent, promising and exciting scientific developments to overcome them.

Organizer:
Cristiana Sebu, University of Malta, Malta, This email address is being protected from spambots. You need JavaScript enabled to view it.


Invited Speakers (in alphabetical order):
Melody Alsaker, Gonzaga University, USA, This email address is being protected from spambots. You need JavaScript enabled to view it.
Ultrasound Data as a Prior in Thoracic Imaging with Electrical Impedance Tomography

Stephan Antholzer, University of Innsbruck, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it.
Learned regularizers for compressed sensing photoacoustic tomography

Tatiana Bubba, University of Helsinki, Finland, This email address is being protected from spambots. You need JavaScript enabled to view it.
Simultaneous reconstruction of emission and attenuation in passive gamma emission tomography of spent nuclear fuel

Sara Garbarino, Université Côte d’Azur, France, This email address is being protected from spambots. You need JavaScript enabled to view it.
Diffusion Tensor Magnetic Resonance and Positron Emission Tomography combined imaging data for reconstructing the progression of neurodegenerative diseases

Esther Klann, Hochschule Merseburg, Germany, This email address is being protected from spambots. You need JavaScript enabled to view it.

Tobias Kluth, University of Bremen, Germany, This email address is being protected from spambots. You need JavaScript enabled to view it.
The calibration problem in magnetic particle imaging: Time-dependent parameter identification in nanoparticles' magnetization dynamics

Peter Maass, University of Bremen, Germany, This email address is being protected from spambots. You need JavaScript enabled to view it.
Analytic approaches combined with deep learning concepts for magnetic particle imaging

Pierre Marechal, Université Paul Sabatier, France, This email address is being protected from spambots. You need JavaScript enabled to view it.

Irina V. Melnikova, Ural State University, Russia, This email address is being protected from spambots. You need JavaScript enabled to view it.
Direct and inverse problems for stochastic processes

Volker Michel, University of Siegen, Germany This email address is being protected from spambots. You need JavaScript enabled to view it.
Geophysical and medical imaging: what they can learn from each other

Lukas Neumann, University of Innsbruck, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it.
Block coordinate descent for inverse problems and application to multi spectral X-ray CT imaging

Daniela Schiefeneder, University of Innsbruck, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it.
On ill-posedness of Volterra integral equations

Aku Seppänen, University of Eastern Finland, Finland, This email address is being protected from spambots. You need JavaScript enabled to view it.
Tomographic imaging of cement-based materials

Alberto Sorrentino, University of Genoa, Italy, This email address is being protected from spambots. You need JavaScript enabled to view it.
A Bayesian approach to sparse imaging with Monte Carlo samplers

Faouzi Triki, Université Grenoble Alpes, France, This email address is being protected from spambots. You need JavaScript enabled to view it.