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    <title>Akkus, Z.</title>
    <link>http://repub.eur.nl/res/aut/54754/</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>
    </image>
    <item>
      <title>Quantitative Analysis of Ultrasound Contrast Flow Behavior in Carotid Plaque Neovasculature (Article)</title>
      <link>http://repub.eur.nl/res/pub/37500/</link>
      <pubDate>2012-10-11T00:00:00Z</pubDate>
      <description>Intraplaque neovascularization is considered as an important indication for plaque vulnerability. We propose a semiautomatic algorithm for quantification of neovasculature, thus, enabling assessment of plaque vulnerability. The algorithm detects and tracks contrast spots using multidimensional dynamic programming. Classification of contrast tracks into blood vessels and artifacts was performed. The results were compared with manual tracking, visual classification and maximal intensity projection. In 28 plaques, 97% of the contrast spots were detected. In 89% of the objects, the automatic tracking determined the contrast motion with an average distance of less than 0.5 mm from the manual marking. Furthermore, 75% were correctly classified into artifacts and vessels. The automated neovascularization grading agreed within 1 grade with visual analysis in 91% of the cases, which was comparable to the interobserver variability of visual grading. These results show that the method can successfully quantify features that are linked to vulnerability of the carotid plaque. </description>
    </item> <item>
      <title>Estimating 3D lumen centerlines of carotid arteries in free-hand acquisition ultrasound (Article)</title>
      <link>http://repub.eur.nl/res/pub/34634/</link>
      <pubDate>2011-06-29T00:00:00Z</pubDate>
      <description>Purpose: The purpose of this paper is to present a methodology to estimate the carotid artery lumen centerlines in ultrasound (US) images obtained in a free-hand examination. Challenging aspects here are speckle noise in US images, artifacts, and the lack of contrast in the direction orthogonal to the US beam direction. Method: An algorithm based on a rough lumen segmentation obtained by robust ellipse fitting was developed to deal with these conditions and estimate the lumen center in 2D B-mode scans. In a free-hand sweep examination, continuous image acquisitions are performed through time when the radiologist moves the probe on the patient's neck. The result is a series of images that show 2D cross-sections of the carotid's morphology. A tracking sensor (Flock of Birds) was attached to the probe and both were connected to a PC executing the Stradwin software, which relates spatial information to the acquisition data of the US probe. The spatial information was combined with the 2D lumen center estimates to provide a centerline in 3D. For validation, 19 carotid scans from 15 different patients were scanned, their centerlines calculated by the algorithm and compared with results acquired by manual annotations. Results: The average Euclidean distance between both among all the examinations was 0.82  mm. For each examination, the percentage of these Euclidean distances below 2  mm was calculated; the average over all examinations was 92%. Conclusion: Automated 3D estimation of carotid artery lumen centerlines in free-hand real-time ultrasound is feasible and can be performed with high accuracy. The algorithm is robust enough to keep the centerlines inside the vessel, even in the absence of contrast in parts of the vessel wall. </description>
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