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Jaume Garcia. (2002)." Propagacio de fronts per a la segmentacio en imatges IVUS" .
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Debora Gil. (2002)." Regularized Curvature Flow" . Computer Vision Centre.
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Debora Gil, & Petia Radeva. (2003)." Curvature based Distance Maps" . Computer Vision Center.
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Ole Larsen, Petia Radeva, & Enric Marti. (1994)." Calculating the Bounds on the Optimal Parameters of Elasticity for a Snake" . Denmark: Aalborg University, Laboratory of image Analysis.
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Jaime Lopez-Krahe, Josep Llados, & Enric Marti. (2000). "Architectural Floor Plan Analysis " (Robert B. Fisher, Ed.). University of Edinburgh.
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Ferran Poveda. (2009). "Visualització i interpretació tridimensional de l’arquitectura de les fibres musculars del miocardi ". Master's thesis, , 08193 Bellaterra, Barcelona (Spain).
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Eric Amiel. (2005). "Visualisation de vaisseaux sanguins " (Enric Marti, Ed.). Bachelor's thesis, Université Paul Sabatier Toulouse III, Toulouse.
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Francesco Brughi. (2013)." Artistic Heritage Motive Retrieval: an Explorative Study" (Vol. 176). Master's thesis, , .
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Aura Hernandez-Sabate, Debora Gil, & Petia Radeva. (2005). "A Deterministic-Statistical Strategy for Adventitia Segmentation in IVUS images ".
Abstract: A useful tool for some specific studies in cardiac disease diagnosis is vessel plaque assessment by analysis of IVUS sequences. Manual detection of luminal (inner) and media-adventitia (external) vessel borders is the main activity of physicians in the process of lumen narrowing (plaque) quantification. Difficult definition of vessel border descriptors, as well as, shades, artifacts and blurred signal response due to ultrasound physical properties troubles automated adventitia segmentation. In order to efficiently approach such a complex problem, we propose blending advanced anisotropic filtering operators and statistical classification techniques into a vessel border modelling strategy. Our systematic statistical analysis shows that the reported adventitia detection achieves an accuracy in the range of inter-observer variability regardless of plaque nature, vessel geometry and incomplete vessel borders.
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Aura Hernandez-Sabate. (2005). "Automatic adventitia segmentation in IntraVascular UltraSound images ". Master's thesis, , 08193 Bellaterra, Barcelona (Spain).
Abstract: A usual tool in cardiac disease diagnosis is vessel plaque assessment by analysis of IVUS sequences. Manual detection of lumen-intima, intima-media and media-adventitia vessel borders is the main activity of physicians in the process of plaque quantification. Large variety in vessel border descriptors, as well as, shades, artifacts and blurred response due to ultrasound physical properties troubles automated media-adventitia segmentation. This experimental work presents a solution to such a complex problem. The process blends advanced anisotropic filtering operators and statistic classification techniques, achieving an efficient vessel border modelling strategy. First of all, we introduce the theoretic base of the method. After that, we show the steps of the algorithm, validating the method with statistics that show that the media-adventitia border detection achieves an accuracy in the range of inter-observer variability regardless of plaque nature, vessel geometry and incomplete vessel borders. Finally, we present a little Matlab application to the automatic media-adventitia border.
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