Multimodal Image Analysis for Carotid Artery Plaque Characterization

Atherosclerosis of the carotid artery is a main cause of ischemic cerebrovascular events. There is evidence that the composition of the vessel wall is more strongly related to plaque vulnerability and subsequent events than luminal stenosis, which is currently used for risk stratification in clinical practice. Noninvasive imaging can characterize the composition of the vessel wall. In order to incorporate measures of plaque composition into clinical practice, accurate and robust image segmentation methods are required. This thesis describes the development and validation of image analysis techniques that aim at the automated characterization of the carotid atherosclerotic vessel wall. The first part of this thesis makes use of a dataset in which ex vivo and in vivo MRI and CT, and annotated histology sections are available and have been spatially aligned. We firstly perform segmentation of plaque components in ex vivo MRI. Voxel classifiers are trained on a ground truth of registered histology and μCT images. We show the importance of different groups of features: intensities, Gaussian filters and wall distances, and use these features in subsequent work on in vivo data. Here we address the problems that arise in training and evaluation of segmentation methods when misregistration between histology and in vivo

ATMOL: A Domain-Specific Language for Atmospheric Modeling

This paper describes the design and implementation of ATMOL: a domain-specific language for the formulation and implementation of atmospheric models. ATMOL was developed in close collaboration with meteorologists at the Royal Netherlands Meteorological Institute (KNMI) to ensure ease of use, concise notation, and the adoptation of common notational conventions. ATMOL’s expressiveness allows the formulation of high-level and low-level model details as language constructs for problem refinement and code synthesis. The atmospheric models specified in ATMOL are translated into efficient numerical codes with CTADEL, a tool for symbolic manipulation and code synthesis

ATMOL: A Domain-Specific Language for Atmospheric Modeling

This paper describes the design and implementation of ATMOL: a domain-specific language for the formulation and implementation of atmospheric models. ATMOL was developed in close collaboration with meteorologists at the Royal Netherlands Meteorological Institute (KNMI) to ensure ease of use, concise notation, and the adoptation of common notational conventions. ATMOL’s expressiveness allows the formulation of high-level and low-level model details as language constructs for problem refinement and code synthesis. The atmospheric models specified in ATMOL are translated into efficient numerical codes with CTADEL, a tool for symbolic manipulation and code synthesis

CMB Lensing Power Spectrum Biases from Galaxies and Clusters using High-angular Resolution Temperature Maps

The lensing power spectrum from cosmic microwave background (CMB) temperature maps will be measured with unprecedented precision with upcoming experiments, including upgrades to ACT and SPT. Achieving significant improvements in cosmological parameter constraints, such as percent level errors on sigma_8 and an uncertainty on the total neutrino mass of approximately 50 meV, requires percent level measurements of the CMB lensing power. This necessitates tight control of systematic biases. We study several types of biases to the temperature-based lensing reconstruction signal from foreground sources such as radio and infrared galaxies and the thermal Sunyaev-Zel'dovich effect from galaxy clusters. These foregrounds bias the CMB lensing signal due to their non-Gaussian nature. Using simulations as well as some analytical models we find that these sources can substantially impact the measured signal if left untreated. However, these biases can be brought to the percent level if one masks galaxies with fluxes at 150 GHz above 1 mJy and galaxy clusters with masses above M_vir = 10^14 M_sun. To achieve such percent level bias, we find that only modes up to a maximum multipole of l_max ~ 2500 should be included in the lensing reconstruction. We also discuss ways to minimize additional bias induced by such aggressive foreground masking by, for example, exploring a two-step masking and in-painting algorithm.Comment: 14 pages, 14 figures, to be submitted to Ap

CMB B -mode non-Gaussianity

We study the degree to which the cosmic microwave background (CMB) can be used to constrain primordial non-Gaussianity involving one tensor and two scalar fluctuations, focusing on the correlation of one polarization B mode with two temperature modes. In the simplest models of inflation, the tensor-scalar-scalar primordial bispectrum is nonvanishing and is of the same order in slow-roll parameters as the scalar-scalar-scalar bispectrumr. We calculate the {BTT} correlation arising from a primordial tensor-scalar-scalar bispectrum, and show that constraints from an experiment like CMB-Stage IV using this observable are more than an order of magnitude better than those on the same primordial coupling obtained from temperature measurements alone. We argue that B-mode non-Gaussianity opens up an as-yet-unexplored window into the early Universe, demonstrating that significant information on primordial physics remains to be harvested from CMB anisotropies

An evaluation of clone detection techniques for identifying crosscutting concerns

Code implementing a crosscutting concern is often spread over many different parts of an application. Identifying such code automatically greatly improves both the maintainability and the evolvability of the application. First of all, it allows a developer to more easily find the places in the code that must be changed when the concern changes, and thus makes such changes less time consuming and less prone to errors. Second, it allows a developer to refactor the code, so that it uses modern and more advanced abstraction mechanisms, thereby restoring its modularity. In this paper, we evaluate the suitability of clone detection as a technique for the identification of crosscutting concerns. To that end, we manually identify four specific concerns in an industrial C application, and analyze to what extent clone detection is capable of finding these concerns. We consider our results as a stepping stone toward an automated 'concern miner' based on clone detection

High Pressure X-Ray Diffraction Study of UMn2Ge2

Uranium manganese germanide, UMn2Ge2, crystallizes in body-centered tetragonal ThCr2Si2 structure with space group I4/mmm, a = 3.993A and c = 10.809A under ambient conditions. Energy dispersive X-ray diffraction was used to study the compression behaviour of UMn2Ge2 in a diamond anvil cell. The sample was studied up to static pressure of 26 GPa and a reversible structural phase transition was observed at a pressure of ~ 16.1 GPa. Unit cell parameters were determined up to 12.4 GPa and the calculated cell volumes were found to be well reproduced by a Murnaghan equation of state with K0 = 73.5 GPa and K' = 11.4. The structure of the high pressure phase above 16.0 GPa is quite complicated with very broad lines and could not be unambiguously determined with the available instrument resolution