Misael Rosales, Petia Radeva, Oriol Rodriguez, & Debora Gil. (2005). Suppression of IVUS Image Rotation. A Kinematic Approach. In Monica Andres and Hernandez Petia and Santos A. and R. Frangi (Ed.), Functional Imaging and Modeling of the Heart (Vol. 3504, pp. 889–892). LNCS, 3504. Springer Berlin / Heidelberg.
Abstract: IntraVascular Ultrasound (IVUS) is an exploratory technique used in interventional procedures that shows cross section images of arteries and provides qualitative information about the causes and severity of the arterial lumen narrowing. Cross section analysis as well as visualization of plaque extension in a vessel segment during the catheter imaging pullback are the technique main advantages. However, IVUS sequence exhibits a periodic rotation artifact that makes difficult the longitudinal lesion inspection and hinders any segmentation algorithm. In this paper we propose a new kinematic method to estimate and remove the image rotation of IVUS images sequences. Results on several IVUS sequences show good results and prompt some of the clinical applications to vessel dynamics study, and relation to vessel pathology.
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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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Oriol Pujol, Debora Gil, & Petia Radeva. (2005). Fundamentals of Stop and Go active models. Image and Vision Computing, 23(8), 681–691.
Abstract: An efficient snake formulation should conform to the idea of picking the smoothest curve among all the shapes approximating an object of interest. In current geodesic snakes, the regularizing curvature also affects the convergence stage, hindering the latter at concave regions. In the present work, we make use of characteristic functions to define a novel geodesic formulation that decouples regularity and convergence. This term decoupling endows the snake with higher adaptability to non-convex shapes. Convergence is ensured by splitting the definition of the external force into an attractive vector field and a repulsive one. In our paper, we propose to use likelihood maps as approximation of characteristic functions of object appearance. The better efficiency and accuracy of our decoupled scheme are illustrated in the particular case of feature space-based segmentation.
Keywords: Deformable models; Geodesic snakes; Region-based segmentation
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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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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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Fernando Lopez, J.M. Valiente, Ramon Baldrich, & Maria Vanrell. (2005). Fast surface grading using color statistics in the CIELab space. In Pattern Recognition and Image Analysis. IbPRIA 2005 (Vol. LNCS 3523, pp. 66–673).
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Niki Aifanti, Angel Sappa, N. Grammalidis, & Sotiris Malassiotis. (2005). Human Motion Tracking and Recognition. In Encyclopedia of Information Science and Technology, 1(5):1355–1360.
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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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Jian Yang, Alejandro F. Frangi, Jing-Yu Yang, David Zhang, & Zhong Jin. (2005). KPCA Plus LDA: A Complete Kernel Fisher Discriminant Framework for Feature Extraction and Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(2):230–244 (IF: 3.810).
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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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Xavier Otazu, & Maria Vanrell. (2005). Perceptual representation of textured images. Journal of Imaging Science and Technology, 49(3):262–271 (IF: 0.522).
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Agata Lapedriza, David Masip, & Jordi Vitria. (2005). Are external face features useful for automatic face classification?.
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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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Xavier Baro. (2005). Fast traffic sign detection on gray-scale images.
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Agata Lapedriza. (2005). Face Classification using External Face Features.
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