CMIC Seminar: Lebina Shrestha Kakkar and Andreas Hauptmann

Speaker: Lebina Shrestha Kakkar and Andreas Hauptmann, UCL-CS
UCL Contact: Dominique Drai (Visitors from outside UCL please email in advance).
Date/Time: 24 May 17, 13:00 - 14:00
Venue: Roberts 106

Abstract

Lebina Shrestha Kakkar

Title: Comparison of OGSE and SDE ActiveAx for axon diameter mapping: An experimental study in viable nerve tissue

Abstract:

Mapping axon diameters within the central and peripheral nervous system could play an important role in our understanding of nerve pathways, and help diagnose and monitor an array of neurological disorders. Numerous diffusion MRI methods have been proposed for imaging axon diameters, most of which use conventional single diffusion encoding (SDE) spin echo sequences. However, a growing number of studies show that oscillating gradient spin echo (OGSE) sequences can provide additional advantages over conventional SDE sequences. Recent theoretical results suggest that this is especially the case in realistic scenarios, such as when fibres have unknown or dispersed orientation. In the seminar I will present some recent work that experimentally investigates the extent of these advantages by comparing the performances of OGSE and SDE in viable nerve tissue. The results will show for the first time in, quantitatively and in an as close as possible to in vivo conditions, that OGSE provides advantages over SDE for axon diameter mapping.

Andreas Hauptmann

Title: A Variational Reconstruction Method for Dynamical X-ray Tomography based on Physical Motion Models

Abstract:

We study the reconstruction of moving object densities from undersampled dynamic X-ray tomography in two dimensions. A particular motivation of this study is to use realistic measurement protocols for practical applications, i.e. we do not assume to have full measurements in each time step, but only projections in few angular directions. This restriction enforces a space-time reconstruction, which we perform by incorporating physical motion models and regularization of motion vectors in a variational framework. The methodology of optical flow, which is one of the most common methods to estimate motion between two images, is utilized to formulate a joint variational model for reconstruction and motion estimation. Results are presented for simulated and real measurement data.