M13. Applications of Rich Tomography 

Traditionally, tomography involves the reconstruction of a scalar function, i.e. an image, from its integrals along lines, or possibly surfaces, passing through a region. Rich tomography is a broad term, referring to a family of methods aiming to reconstruct a more complicated object, such as a vector or tensor field, using additional data, such as travel time, energy, or frequency, along curves or curved surfaces. Many problems with important applications fit under this umbrella including spectral CT, Neutron polarimetric and Bragg edge tomography, various types of emission tomography including that arising in range verification for proton therapy, and in synthetic aperture radar.

This mini-symposium will examine such applications, looking at the similar mathematical techniques which unite them.

Organizers:
Sean Holman, The University of Manchester, UK, This email address is being protected from spambots. You need JavaScript enabled to view it.                                                  
William Robert Breckon Lionheart, The University of Manchester, UK This email address is being protected from spambots. You need JavaScript enabled to view it.    

Invited Speakers:
Amal M. A. Alghamdi, Technical University of Denmark, This email address is being protected from spambots. You need JavaScript enabled to view it.
Computational Uncertainty Quantification for Inverse problems in Python (CUQIpy)

Margaret Duff, STFC – Rutherford Appleton Laboratories, UK, This email address is being protected from spambots. You need JavaScript enabled to view it.
Rich and Non-Rich Tomography - a multidisciplinary approach using the Core Imaging Library

Shubham Ramkisan Jathar, LUT University, Finland; Indian Institute of Science Education and Research (IISER), India, This email address is being protected from spambots. You need JavaScript enabled to view it.
Normal operators for momentum ray transforms

Paul David Ledger, Keele University, UK, This email address is being protected from spambots. You need JavaScript enabled to view it.
Object characterisation and Bayesian classification in metal detection

William Robert Breckon Lionheart, The University of Manchester, UK, This email address is being protected from spambots. You need JavaScript enabled to view it.
Neutron strain topography

Jesse Railo, LUT University, Finland, This email address is being protected from spambots. You need JavaScript enabled to view it.
Magnetic and thermostatic nonabelian ray transforms