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Jordi Gonzalez, J. Varona, Xavier Roca, & Juan J. Villanueva. (2005). A Comparison Framework for Walking Performances using aSpaces. Electronic Letters on Computer Vision and Image Analysis, Special Issue on articulated Motion, 5(3):105–116 (Electronic Letters: IF: 1.016).
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Quan-sen Sun, Pheng-ann Heng, Zhong Jin, & De-shen Xia. (2005). Face recognition based on generalized canonical correlation analysis. In Advances in Intelligent Computing, Lecture Notes in Computer Science, 3645: 958–967.
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Quan-sen Sun, Zhong Jin, Pheng-ann Heng, & De-shen Xia. (2005). A novel feature fusion method based on partial least squares regression. In Pattern Recognition and Data Mining, Lecture Notes in Computer Science, 3686: 268–277.
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Zhong Jin, Zhen Lou, Jing-Yu Yang, & Quan-sen Sun. (2005). Face detection using template matching and skin color information.
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Zhong Jin, Jing-Yu Yang, & Zhen Lou. (2005). A luminance-conditional distribution model of skin color information.
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Jaume Garcia, Joel Barajas, Francesc Carreras, Sandra Pujades, & Petia Radeva. (2005). An intuitive validation technique to compare local versus global tagged MRI analysis. In Computers In Cardiology (Vol. 32, 29–32).
Abstract: Myocardium appears as a uniform tissue that seen in convectional Magnetic Resonance Images (MRI) shows just the contractile part of its movement. MR Tagging is a unique imaging technique that prints a grid over the tissue which moves according to the underlying movement of the myocardium revealing the true deformation of the cardiac muscle. Optical flow techniques based on spectral information estimate tissue displacement by analyzing information encoded in the phase maps which can be obtained using, local (Gabor) and global (HARP) methods. In this paper we compare both in synthetic and real Tagged MR sequences. We conclude that local method is slightly more accurate than the global one. On the other hand, global method is more efficient as it is much faster and less parameters have to be taken into account
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F. Lopez, J.M. Valiente, Ramon Baldrich, & Maria Vanrell. (2005). Fast surface grading using color statistics in the CIELab space. In LNCS 1: 666–673.
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Oriol Ramos Terrades, & Ernest Valveny. (2005). Local Norm Features based on ridgelets Transform.
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J. Nuñez, Xavier Otazu, & M.T. Merino. (2005). A Multiresolution-Based Method for the Determination of the Relative Resolution between Images. First Application to Remote Sensing and Medical Images. International Journal of Imaging Systems and Technology, 15(5): 225–235 (IF: 0.439).
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Miquel Ferrer, F. Serratosa, & A. Sanfeliu. (2005). Synthesis of median spectral graph. In Pattern Recognition and Image Analysis (IbPRIA´05), LNCS, 3523: 139 146.
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Debora Gil, Aura Hernandez-Sabate, Antoni Carol, Oriol Rodriguez, & Petia Radeva. (2005). A Deterministic-Statistic Adventitia Detection in IVUS Images. In ESC Congress. ,Sweden (EU).
Abstract: Plaque analysis in IVUS planes needs accurate intima and adventitia models. Large variety in adventitia descriptors difficulties its detection and motivates using a classification strategy for selecting points on the structure. Whatever the set of descriptors used, the selection stage suffers from fake responses due to noise and uncompleted true curves. In order to smooth background noise while strengthening responses, we apply a restricted anisotropic filter that homogenizes grey levels along the image significant structures. Candidate points are extracted by means of a simple semi supervised adaptive classification of the filtered image response to edge and calcium detectors. The final model is obtained by interpolating the former line segments with an anisotropic contour closing technique based on functional extension principles.
Keywords: Electron microscopy; Unbending; 2D crystal; Interpolation; Approximation
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Debora Gil, Aura Hernandez-Sabate, Antoni Carol, Oriol Rodriguez, & Petia Radeva. (2005). A Deterministic-Statistic Adventitia Detection in IVUS Images. In 3rd International workshop on International Workshop on Functional Imaging and Modeling of the Heart (pp. 65–74).
Abstract: Plaque analysis in IVUS planes needs accurate intima and adventitia models. Large variety in adventitia descriptors difficulties its detection and motivates using a classification strategy for selecting points on the structure. Whatever the set of descriptors used, the selection stage suffers from fake responses due to noise and uncompleted true curves. In order to smooth background noise while strengthening responses, we apply a restricted anisotropic filter that homogenizes grey levels along the image significant structures. Candidate points are extracted by means of a simple semi supervised adaptive classification of the filtered image response to edge and calcium detectors. The final model is obtained by interpolating the former line segments with an anisotropic contour closing technique based on functional extension principles.
Keywords: Electron microscopy; Unbending; 2D crystal; Interpolation; Approximation
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Debora Gil, & Petia Radeva. (2005). Extending anisotropic operators to recover smooth shapes. Computer Vision and Image Understanding, 99(1), 110–125.
Abstract: Anisotropic differential operators are widely used in image enhancement processes. Recently, their property of smoothly extending functions to the whole image domain has begun to be exploited. Strong ellipticity of differential operators is a requirement that ensures existence of a unique solution. This condition is too restrictive for operators designed to extend image level sets: their own functionality implies that they should restrict to some vector field. The diffusion tensor that defines the diffusion operator links anisotropic processes with Riemmanian manifolds. In this context, degeneracy implies restricting diffusion to the varieties generated by the vector fields of positive eigenvalues, provided that an integrability condition is satisfied. We will use that any smooth vector field fulfills this integrability requirement to design line connection algorithms for contour completion. As application we present a segmenting strategy that assures convergent snakes whatever the geometry of the object to be modelled is.
Keywords: Contour completion; Functional extension; Differential operators; Riemmanian manifolds; Snake segmentation
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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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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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