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Dani Rowe, Ignasi Rius, Jordi Gonzalez, & Juan J. Villanueva. (2005). Improving Tracking by Handling Occlusions.
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Dani Rowe. (2005). Probabilistic Image-based Tracking in Complex Human Environments.
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Cristina Cañero, Nikolaos Thomos, George A. Triantafyllid, George C. Litos, & Michael G. Strintzis. (2005). Mobile Tele-echography: User Interface Design. IEEE Transactions on Information Technology in Biomedicine, 9(1):44–49 (IF: 1.376).
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Bogdan Raducanu, & Jordi Vitria. (2005). Real-Time Face Tracking for Context-Aware Computing.
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Bogdan Raducanu, & Jordi Vitria. (2005). Real-Time Face Tracking for Context-Aware Computing. In Artificial Intelligence Research and Development, IOS Press, 91–98.
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Bogdan Raducanu, & Jordi Vitria. (2005). A Robust Particle Filter-based Face Tracker Using a Combination of Color and Geometric Information.
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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, Debora Gil, & Petia Radeva. (2005). On the usefulness of supervised learning for vessel border detection in IntraVascular Imaging. In Proceeding of the 2005 conference on Artificial Intelligence Research and Development (pp. 67–74). Amsterdam, The Netherlands: IOS Press.
Abstract: IntraVascular UltraSound (IVUS) imaging is a useful tool in diagnosis of cardiac diseases since sequences completely show the morphology of coronary vessels. Vessel borders detection, especially the external adventitia layer, plays a central role in morphological measures and, thus, their segmentation feeds development of medical imaging techniques. Deterministic approaches fail to yield optimal results due to the large amount of IVUS artifacts and vessel borders descriptors. We propose using classification techniques to learn the set of descriptors and parameters that best detect vessel borders. Statistical hypothesis test on the error between automated detections and manually traced borders by 4 experts show that our detections keep within inter-observer variability.
Keywords: classification; vessel border modelling; IVUS
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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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Antonio Lopez, Joan Serrat, J. Saludes, Cristina Cañero, Felipe Lumbreras, & T. Graf. (2005). Ridgeness for Detecting Lane Markings.
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Antonio Lopez, Ernest Valveny, & Juan J. Villanueva. (2005). Real-time quality control of surgical material packaging by artificial vision. Assembly Automation, 25(3).
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Antonio Lopez, Cristina Cañero, Joan Serrat, J. Saludes, Felipe Lumbreras, & T. Graf. (2005). Detection of lane markings based on ridgeness and RANSAC.
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Anton Cervantes, Gemma Sanchez, Josep Llados, Agnes Borras, & A. Rodriguez. (2005). Biometric Recognition Based on Line Shape Descriptors. In Sixth IAPR International Workshop on Graphics Recognition (GREC 2005) (335–344).
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Anton Cervantes. (2005). Biometric Newborn Identification.
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Angel Sappa, Niki Aifanti, Sotiris Malassiotis, & N. Grammalidis. (2005). Survey of 3D Human Body Representations. In Encyclopedia of Information Science and Technology, 1(5):2696–2701.
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