Computational spatiotemporal analysis identifies WAVE2 and cofilin as joint regulators of costimulation-mediated T cell actin dynamics

Fluorescence microscopy is one of the most important tools in cell biology research and it provides spatial and temporal information to investigate regulatory systems inside cells. This technique can generate data in the form of signal intensities at thousands of positions resolved inside individual live cells; however, given extensive cell-to-cell variation, methods do not currently exist to assemble these data into three- or four-dimensional maps of protein concentration that can be compared across different cells and conditions. Here, we have developed one such method and applied it to investigate actin dynamics in T cell activation. Antigen recognition in T cells by the T cell receptor (TCR) is amplified by engagement of the costimulatory receptor CD28 and we have determined how CD28 modulates actin dynamics. We imaged actin and eight core actin regulators under conditions where CD28 in the context of a strong TCR signal was engaged or blocked to yield over a thousand movies. Our computational analysis identified diminished recruitment of the activator of actin nucleation WAVE2 and the actin severing protein cofilin to F-actin as the dominant difference upon costimulation blockade. Reconstitution of WAVE2 and cofilin activity restored the defect in actin signaling dynamics upon costimulation blockade. Thus we have developed and validated an approach to quantify protein distributions in time and space for analysis of complex regulatory systems

Reconstruction of Patient-Specific Bone Models from X-Ray Radiography

The availability of a patient‐specific bone model has become an increasingly invaluable addition to orthopedic case evaluation and planning [1]. Utilized within a wide range of specialized visualization and analysis tools, such models provide unprecedented wealth of bone shape information previously unattainable using traditional radiographic imaging [2]. In this work, a novel bone reconstruction method from two or more x‐ray images is described. This method is superior to previous attempts in terms of accuracy and repeatability. The new technique accurately models the radiological scene in a way that eliminates the need for expensive multi‐planar radiographic imaging systems. It is also flexible enough to allow for both short and long film imaging using standard radiological protocols, which makes the technology easily utilized in standard clinical setups

Virtuelle endovaskuläre Versorgung von abdominalen Aortenaneurysmen

This thesis is focused on computational methods that predict the outcome of endovascular repair of abdominal aortic aneurysms. Novelties include improvements of the aneurysm model, the stent-graft model as well as the in-silico stent-graft placement methodology. The newly developed methods are applied to patient-specific cases and are validated against real-world postinterventional data. Further, directions for using the in-silico model of endovascular aneurysm repair as personalized preinterventional planning tool in clinical practice are provided.Die vorliegende Arbeit beschäftigt sich mit numerischen Methoden um den Ausgang einer endovaskulären Versorgung von abdominalen Aortenaneurysmen vorherzusagen. Neuheiten umfassen Verbesserungen des Aneurysmenmodells, des Stentgraftmodells sowie der virtuellen Platzierungsmethode des Stentgrafts. Die neu entwickelten Methoden werden auf patientenspezifische Fälle angewandt und werden mit realen postoperativen Daten validiert. Weiterhin werden klinische Anwendungen des Modells der endovaskulären Aneurysmenversorgung als personalisiertes präoperatives Planungswerkzeug präsentiert

Tangent-ball techniques for shape processing

Shape processing defines a set of theoretical and algorithmic tools for creating, measuring and modifying digital representations of shapes.  Such tools are of paramount importance to many disciplines of computer graphics, including modeling, animation, visualization, and image processing.  Many applications of shape processing can be found in the entertainment and medical industries. In an attempt to improve upon many previous shape processing techniques, the present thesis explores the theoretical and algorithmic aspects of a difference measure, which involves fitting a ball (disk in 2D and sphere in 3D) so that it has at least one tangential contact with each shape and the ball interior is disjoint from both shapes. We propose a set of ball-based operators and discuss their properties, implementations, and applications.  We divide the group of ball-based operations into unary and binary as follows: Unary operators include: * Identifying details (sharp, salient features, constrictions) * Smoothing shapes by removing such details, replacing them by fillets and roundings * Segmentation (recognition, abstract modelization via centerline and radius variation) of tubular structures Binary operators include: * Measuring the local discrepancy between two shapes * Computing the average of two shapes * Computing point-to-point correspondence between two shapes * Computing circular trajectories between corresponding points that meet both shapes at right angles * Using these trajectories to support smooth morphing (inbetweening) * Using a curve morph to construct surfaces that interpolate between contours on consecutive slices The technical contributions of this thesis focus on the implementation of these tangent-ball operators and their usefulness in applications of shape processing. We show specific applications in the areas of animation and computer-aided medical diagnosis.  These algorithms are simple to implement, mathematically elegant, and fast to execute.Ph.D.Committee Chair: Jarek Rossignac; Committee Member: Greg Slabaugh; Committee Member: Greg Turk; Committee Member: Karen Liu; Committee Member: Maryann Simmon

Virtuelle endovaskuläre Versorgung von abdominalen Aortenaneurysmen

This thesis is focused on computational methods that predict the outcome of endovascular repair of abdominal aortic aneurysms. Novelties include improvements of the aneurysm model, the stent-graft model as well as the in-silico stent-graft placement methodology. The newly developed methods are applied to patient-specific cases and are validated against real-world postinterventional data. Further, directions for using the in-silico model of endovascular aneurysm repair as personalized preinterventional planning tool in clinical practice are provided.Die vorliegende Arbeit beschäftigt sich mit numerischen Methoden um den Ausgang einer endovaskulären Versorgung von abdominalen Aortenaneurysmen vorherzusagen. Neuheiten umfassen Verbesserungen des Aneurysmenmodells, des Stentgraftmodells sowie der virtuellen Platzierungsmethode des Stentgrafts. Die neu entwickelten Methoden werden auf patientenspezifische Fälle angewandt und werden mit realen postoperativen Daten validiert. Weiterhin werden klinische Anwendungen des Modells der endovaskulären Aneurysmenversorgung als personalisiertes präoperatives Planungswerkzeug präsentiert

A Variational Model for Object Segmentation Using Boundary Information and Shape Prior Driven by the Mumford-Shah Functional

In this paper, we propose a new variational model to segment an object belonging to a given shape space using the active contour method, a geometric shape prior and the Mumford-Shah functional. The core of our model is an energy functional composed by three complementary terms. The first one is based on a shape model which constrains the active contour to get a shape of interest. The second term detects object boundaries from image gradients. And the third term drives globally the shape prior and the active contour towards a homogeneous intensity region. The segmentation of the object of interest is given by the minimum of our energy functional. This minimum is computed with the calculus of variations and the gradient descent method that provide a system of evolution equations solved with the well-known level set method. We also prove the existence of this minimum in the space of functions with bounded variation. Applications of the proposed model are presented on synthetic and medical image

Grid simulation services for the medical community

The first part of this paper presents a selection of medical simulation applications, including image reconstruction, near real-time registration for neuro-surgery, enhanced dose distribution calculation for radio-therapy, inhaled drug delivery prediction, plastic surgery planning and cardio-vascular system simulation. The latter two topics are discussed in some detail. In the second part, we show how such services can be made available to the clinical practitioner using Grid technology. We discuss the developments and experience made during the EU project GEMSS, which provides reliable, efficient, secure and lawful medical Grid services