Automated Quantification of Atherosclerosis in CTA of Carotid Arteries

How is the human body built and how does it function? What are the causes of disease, and where is disease located? Throughout the history of mankind these questions were answered by the use of invasive methods that included the “opening” of the human body, mainly cadavers. Thanks to these invasive techniques the first precise and complete anatomy works started to appear in the 16th century. The most influential works were published by Leonardo da Vinci and the anatomist and physician Andreas Vesalius. The discovery of X-rays in 1895, and their use for medical applications, introduced a new era, in which non-invasive imaging of the functioning human body became feasible. Nowadays, medical imaging includes many different imaging modalities, such as X-ray, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US), nuclear and optical imaging, and has become an indispensable diagnostic tool for a wide range of applications. Initially, the application of medical imaging focused on the visualization of anatomy and on the detection and localization of disease. However, with the development of different modalities it has evolved into a much more versatile tool providing important information on e.g. physiology and organ function, biochemistry and metabolism using nuclear imaging (mainly positron emission tomography (PET) imaging), molecular and processes on the molecular and cellular level using molecular imaging techniques

Edge Detection by Adaptive Splitting II. The Three-Dimensional Case

In Llanas and Lantarón, J. Sci. Comput. 46, 485–518 (2011) we proposed an algorithm (EDAS-d) to approximate the jump discontinuity set of functions defined on subsets of ℝ d . This procedure is based on adaptive splitting of the domain of the function guided by the value of an average integral. The above study was limited to the 1D and 2D versions of the algorithm. In this paper we address the three-dimensional problem. We prove an integral inequality (in the case d=3) which constitutes the basis of EDAS-3. We have performed detailed computational experiments demonstrating effective edge detection in 3D function models with different interface topologies. EDAS-1 and EDAS-2 appealing properties are extensible to the 3D cas

Insight into Carotid Atherosclerotic Plaque Development with CT Angiography

Stroke is a leading cause of mortality and morbidity. Atherosclerotic disease of the carotid arteries is an important cause of ischemic stroke. The general aim of this thesis is to contribute to the knowledge on the pathophysiology of atherosclerosis by means of imaging of the atherosclerotic carotid plaque in vivo. This thesis focusses on: - Quantification of imaging biomarkers of carotid atherosclerotic disease with CT angiography; - The investigation on the role of carotid plaque surface (i.e. ulceration) as an imaging biomarker of plaque instability; - The study of plaque development and its determinants using serial CTA imaging

Segmentation of the outer vessel wall of the common carotid artery in CTA.

Item does not contain fulltextA novel method is presented for carotid artery vessel wall segmentation in computed tomography angiography (CTA) data. First the carotid lumen is semi-automatically segmented using a level set approach initialized with three seed points. Subsequently, calcium regions located within the vessel wall are automatically detected and classified using multiple features in a GentleBoost framework. Calcium regions segmentation is used to improve localization of the outer vessel wall because it is an easier task than direct outer vessel wall segmentation. In a third step, pixels outside the lumen area are classified as vessel wall or background, using the same GentleBoost framework with a different set of image features. Finally, a 2-D ellipse shape deformable model is fitted to a cost image derived from both the calcium and vessel wall classifications. The method has been validated on a dataset of 60 CTA images. The experimental results show that the accuracy of the method is comparable to the interobserver variability.01 januari 201