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    <title>Vukadinovic, D.</title>
    <link>http://repub.eur.nl/res/aut/24137/</link>
    <description>List of Publications</description>
    <language>en</language>
    <image>
      <url>http://repub.eur.nl/static-eur/img/logo.png</url>
      <title>RePub, Erasmus University Rotterdam</title>
      <link>http://repub.eur.nl</link>
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    <item>
      <title>Automated Quantification of Atherosclerosis in CTA of Carotid Arteries (Doctoral Thesis)</title>
      <link>http://repub.eur.nl/res/pub/32465/</link>
      <pubDate>2012-05-24T00:00:00Z</pubDate>
      <description>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.</description>
    </item> <item>
      <title>Region based level set segmentation of the outer wall of the carotid bifurcation in CTA (Article)</title>
      <link>http://repub.eur.nl/res/pub/26108/</link>
      <pubDate>2011-06-09T00:00:00Z</pubDate>
      <description>This paper presents a level set based method for segmenting the outer vessel wall and plaque components of the carotid artery in CTA. The method employs a GentleBoost classification framework that classifies pixels as calcified region or not, and inside or outside the vessel wall. The combined result of both classifications is used to construct a speed function for level set based segmentation of the outer vessel wall; the segmented lumen is used to initialize the level set. The method has been optimized on 20 datasets and evaluated on 80 datasets for which manually annotated data was available as reference. The average Dice similarity of the outer vessel wall segmentation was 92%, which compares favorably to previous methods. </description>
    </item> <item>
      <title>Automated versus manual segmentation of atherosclerotic carotid plaque volume and components in CTA: associations with cardiovascular risk factors (Article)</title>
      <link>http://repub.eur.nl/res/pub/26312/</link>
      <pubDate>2011-05-26T00:00:00Z</pubDate>
      <description>The purpose of this study was to validate automated atherosclerotic plaque measurements in carotid arteries from CT angiography (CTA). We present an automated method (three initialization points are required) to measure plaque components within the carotid vessel wall in CTA. Plaque components (calcifications, fibrous tissue, lipids) are determined by different ranges of Hounsfield Unit values within the vessel wall. On CTA scans of 40 symptomatic patients with atherosclerotic plaque in the carotid artery automatically segmented plaque volume, calcified, fibrous and lipid percentages were 0.97 ± 0.51 cm3, 10 ± 11%, 63 ± 10% and 25 ± 5%; while manual measurements by first observer were 0.95 ± 0.60 cm3, 14 ± 16%, 63 ± 13% and 21 ± 9%, respectively and manual measurement by second observer were 1.05 ± 0.75 cm3, 11 ± 12%, 61 ± 11% and 27 ± 10%. In 90 datasets, significant associations were found between age, gender, hypercholesterolemia, diabetes, smoking and previous cerebrovascular disease and plaque features. For both automated and manual measurements, significant associations were found between: age and calcium and fibrous tissue percentage; gender and plaque volume and lipid percentage; diabetes and calcium, smoking and plaque volume; previous cerebrovascular disease and plaque volume. Significant associations found only by the automated method were between age and plaque volume, hypercholesterolemia and plaque volume and diabetes and fibrous tissue percentage. Significant association found only by the manual method was between previous cerebrovascular disease and percentage of fibrous tissue. Automated analysis of plaque composition in the carotid arteries is comparable with the manual analysis and has the potential to replace it. </description>
    </item> <item>
      <title>Robust CTA lumen segmentation of the atherosclerotic carotid artery bifurcation in a large patient population (Article)</title>
      <link>http://repub.eur.nl/res/pub/20478/</link>
      <pubDate>2010-12-01T00:00:00Z</pubDate>
      <description>We propose and validate a semi-automatic method for lumen segmentation of the carotid bifurcation in computed tomography angiography (CTA). First, the central vessel axis is obtained using path tracking between three user-defined points. Second, starting from this path, the segmentation is automatically obtained using a level set. The cost and speed functions for path tracking and segmentation make use of intensity and homogeneity slice-based image features. The method is validated on a large data set of 234 carotid bifurcations of 129 ischemic stroke patients with atherosclerotic disease. The results are compared to manually obtained lumen segmentations. Parameter optimization is carried out on a subset of 30 representative carotid bifurcations. With the optimized parameter settings the method successfully tracked the central vessel paths in 201 of the remaining 204 bifurcations (99%) which were not part of the training set. Comparison with manually drawn segmentations shows that the average overlap between the method and observers is similar (for the inter-observer set the results were 92% vs. 87% and for the intra-observer set 94% vs. 94%). Therefore the method has potential to replace the manual procedure of lumen segmentation of the atherosclerotic bifurcation in CTA. © 2010 Elsevier B.V.</description>
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