3D reconstruction of cerebral blood flow and vessel morphology from x-ray rotational angiography

Three-dimensional (3D) information on blood flow and vessel morphology is important when assessing cerebrovascular disease and when monitoring interventions. Rotational angiography is nowadays routinely used to determine the geometry of the cerebral vasculature. To this end, contrast agent is injected into one of the supplying arteries and the x-ray system rotates around the head of the patient while it acquires a sequence of x-ray images. Besides information on the 3D geometry, this sequence also contains information on blood flow, as it is possible to observe how the contrast agent is transported by the blood. The main goal of this thesis is to exploit this information for the quantitative analysis of blood flow. I propose a model-based method, called flow map fitting, which determines the blood flow waveform and the mean volumetric flow rate in the large cerebral arteries. The method uses a model of contrast agent transport to determine the flow parameters from the spatio-temporal progression of the contrast agent concentration, represented by a flow map. Furthermore, it overcomes artefacts due to the rotation (overlapping vessels and foreshortened vessels at some projection angles) of the c-arm using a reliability map. For the flow quantification, small changes to the clinical protocol of rotational angiography are desirable. These, however, hamper the standard 3D reconstruction. Therefore, a new method for the 3D reconstruction of the vessel morphology which is tailored to this application is also presented. To the best of my knowledge, I have presented the first quantitative results for blood flow quantification from rotational angiography. Additionally, the model-based approach overcomes several problems which are known from flow quantification methods for planar angiography. The method was mainly validated on images from different phantom experiments. In most cases, the relative error was between 5% and 10% for the volumetric mean flow rate and between 10% and 15% for the blood flow waveform. Additionally, the applicability of the flow model was shown on clinical images from planar angiographic acquisitions. From this, I conclude that the method has the potential to give quantitative estimates of blood flow parameters during cerebrovascular interventions

Electronic transport in high magnetic fields of thin film MnSi

We present a study of the magnetoresistivity of thin film MnSi in high magnetic fields.Weestablish that the magnetoresistivity can be understood in terms of spin fluctuation theory, allowing us to compare our data to studies of bulk material. Despite of a close qualitative resemblance of bulk and thin film data, there are clear quantitative differences.Wepropose that these reflect a difference of the spin fluctuation spectra in thin film and bulk material MnSi, and discuss possible causes

Estimation of valvular resistance of segmented aortic valves using computational fluid dynamics

Aortic valve stenosis is associated with an elevated left ventricular pressure and transaortic pressure drop. Clinicians routinely use Doppler ultrasound to quantify aortic valve stenosis severity by estimating this pressure drop from blood velocity. However, this method approximates the peak pressure drop, and is unable to quantify the partial pressure recovery distal to the valve. As pressure drops are flow dependent, it remains difficult to assess the true significance of a stenosis for low-flow low-gradient patients. Recent advances in segmentation techniques enable patient-specific Computational Fluid Dynamics (CFD) simulations of flow through the aortic valve. In this work a simulation framework is presented and used to analyze data of 18 patients. The ventricle and valve are reconstructed from 4D Computed Tomography imaging data. Ventricular motion is extracted from the medical images and used to model ventricular contraction and corresponding blood flow through the valve. Simplifications of the framework are assessed by introducing two simplified CFD models: a truncated time-dependent and a steady-state model. Model simplifications are justified for cases where the simulated pressure drop is above 10 mmHg. Furthermore, we propose a valve resistance index to quantify stenosis severity from simulation results. This index is compared to established metrics for clinical decision making, i.e. blood velocity and valve area. It is found that velocity measurements alone do not adequately reflect stenosis severity. This work demonstrates that combining 4D imaging data and CFD has the potential to provide a physiologically relevant diagnostic metric to quantify aortic valve stenosis severity

Incompressible image registration using divergence-conforming B-splines

Anatomically plausible image registration often requires volumetric preservation. Previous approaches to incompressible image registration have exploited relaxed constraints, ad hoc optimisation methods or practically intractable computational schemes. Divergence-free velocity fields have been used to achieve incompressibility in the continuous domain, although, after discretisation, no guarantees have been provided. In this paper, we introduce stationary velocity fields (SVFs) parameterised by divergence-conforming B-splines in the context of image registration. We demonstrate that sparse linear constraints on the parameters of such divergence-conforming B-Splines SVFs lead to being exactly divergence-free at any point of the continuous spatial domain. In contrast to previous approaches, our framework can easily take advantage of modern solvers for constrained optimisation, symmetric registration approaches, arbitrary image similarity and additional regularisation terms. We study the numerical incompressibility error for the transformation in the case of an Euler integration, which gives theoretical insights on the improved accuracy error over previous methods. We evaluate the proposed framework using synthetically deformed multimodal brain images, and the STACOM11 myocardial tracking challenge. Accuracy measurements demonstrate that our method compares favourably with state-of-the-art methods whilst achieving volume preservation.Comment: Accepted at MICCAI 201

Deep execution monitor for robot assistive tasks

We consider a novel approach to high-level robot task execution for a robot assistive task. In this work we explore the problem of learning to predict the next subtask by introducing a deep model for both sequencing goals and for visually evaluating the state of a task. We show that deep learning for monitoring robot tasks execution very well supports the interconnection between task-level planning and robot operations. These solutions can also cope with the natural non-determinism of the execution monitor. We show that a deep execution monitor leverages robot performance. We measure the improvement taking into account some robot helping tasks performed at a warehouse

Charge transport through single molecules, quantum dots, and quantum wires

We review recent progresses in the theoretical description of correlation and quantum fluctuation phenomena in charge transport through single molecules, quantum dots, and quantum wires. A variety of physical phenomena is addressed, relating to co-tunneling, pair-tunneling, adiabatic quantum pumping, charge and spin fluctuations, and inhomogeneous Luttinger liquids. We review theoretical many-body methods to treat correlation effects, quantum fluctuations, nonequilibrium physics, and the time evolution into the stationary state of complex nanoelectronic systems.Comment: 48 pages, 14 figures, Topical Review for Nanotechnolog

The <i>Castalia</i> mission to Main Belt Comet 133P/Elst-Pizarro

We describe Castalia, a proposed mission to rendezvous with a Main Belt Comet (MBC), 133P/Elst-Pizarro. MBCs are a recently discovered population of apparently icy bodies within the main asteroid belt between Mars and Jupiter, which may represent the remnants of the population which supplied the early Earth with water. Castalia will perform the first exploration of this population by characterising 133P in detail, solving the puzzle of the MBC’s activity, and making the first in situ measurements of water in the asteroid belt. In many ways a successor to ESA’s highly successful Rosetta mission, Castalia will allow direct comparison between very different classes of comet, including measuring critical isotope ratios, plasma and dust properties. It will also feature the first radar system to visit a minor body, mapping the ice in the interior. Castalia was proposed, in slightly different versions, to the ESA M4 and M5 calls within the Cosmic Vision programme. We describe the science motivation for the mission, the measurements required to achieve the scientific goals, and the proposed instrument payload and spacecraft to achieve these

A monotone multigrid solver for two body contact problems in biomechanics

The purpose of the paper is to apply monotone multigrid methods to static and dynamic biomechanical contact problems. In space, a finite element method involving a mortar discretization of the contact conditions is used. In time, a new contact-stabilized Newmark scheme is presented. Numerical experiments for a two body Hertzian contact problem and a biomechanical application are reported