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Descripción Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -We present a new method for the segmentation and the detection of human Abdominal Aorta in CT images. Our method is divided into two parts. In the first part we estimate the position and the dimension of the aortic lumen using state-of-the-art object tracking techniques. The second part employs curve fitting methods in order to detect the boundaries of the aortic lumen with accuracy, based on the estimation of the first part. In particular, the proposed method uses the Kalman Filter to track the aortic cross-section in consecutive CT images. The observations needed by the Kalman procedure are extracted with the Circle Hough Transformation, based on the assumption that the morphological structure of the aortic cross-section is approximately a circle. A robust Level Set method is then applied to compensate the approximation error and efficiently estimate the cross-section. The algorithms and the mathematical tools developed during the project prove feasibility for an accurate and reliable method for the segmentation of the abdominal aorta from CT data, that in the future could be used to benefit patients with aortic aneurysms. 72 pp. Englisch. Nº de ref. del artículo: 9783844397208
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Descripción Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - We present a new method for the segmentation and the detection of human Abdominal Aorta in CT images. Our method is divided into two parts. In the first part we estimate the position and the dimension of the aortic lumen using state-of-the-art object tracking techniques. The second part employs curve fitting methods in order to detect the boundaries of the aortic lumen with accuracy, based on the estimation of the first part. In particular, the proposed method uses the Kalman Filter to track the aortic cross-section in consecutive CT images. The observations needed by the Kalman procedure are extracted with the Circle Hough Transformation, based on the assumption that the morphological structure of the aortic cross-section is approximately a circle. A robust Level Set method is then applied to compensate the approximation error and efficiently estimate the cross-section. The algorithms and the mathematical tools developed during the project prove feasibility for an accurate and reliable method for the segmentation of the abdominal aorta from CT data, that in the future could be used to benefit patients with aortic aneurysms. Nº de ref. del artículo: 9783844397208
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Descripción Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Koulouri AlexandraAlexandra Koulouri graduated from the school of Electrical Eng., Aristotle Univ. of Thessaloniki(2007). She obtained her Msc degree(2007-08 IC London) in Signal Proc. and in 2008-09 she completed the postgraduate bi. Nº de ref. del artículo: 5477188