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Maya Dimitrova, Petia Radeva, David Rotger, D. Boyadjiev, & Juan J. Villanueva. (2004). Advanced Cardiological Diagnosis via Intelligent Image Analysis.
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Oriol Pujol, Oriol Rodriguez-Leor, J. Mauri, E. Fernandez, V. Valle, & Petia Radeva. (2004). Automatic segmentation and characterization of IVUS images by texture analysis.
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O. Rodriguez, David Rotger, J. Mauri, E. Fernandez, V. Valle, & Petia Radeva. (2004). Active vessel workstation: three-dimensional reconstruction of coronary arteries by fusion of angiography and intravascular ultrasound.
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Jian Yang, Zhong Jin, Jing-Yu Yang, David Zhang, & Alejandro F. Frangi. (2004). Essence of kernel Fisher discriminant: KPCA plus LDA. Pattern Recognition, 37(10): 2097–2100 (IF: 2.176).
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Yong Xu, Jing-Yu Yang, & Zhong Jin. (2004). A novel method for Fisher discriminant analysis. Pattern Recognition, 37(2):381–384 (IF: 2.176).
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Zhong Jin, Franck Davoine, & Zhen Lou. (2004). An Effective EM Algorithm for PCA Mixture Model.
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Antonio Lopez, Felipe Lumbreras, Joan Serrat, & Juan J. Villanueva. (1999). Evaluation of Methods for Ridge and Valley Detection.
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Robert Benavente, Maria Vanrell, & Ramon Baldrich. (2004). Estimation of Fuzzy Sets for Computational Colour Categorization. Color Research and Application, 29(5):342–353 (IF: 0.739).
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A.F. Sole, Antonio Lopez, & G. Sapiro. (2001). Crease Enhancement Diffusion. Computer Vision and Image Understanding, 84(2): 241–248 (IF: 1.298), .
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A. Pujol, Antonio Lopez, Jose Luis Alba, & Juan J. Villanueva. (2001). Ridges, Valleys and Hausdorff Based Similarity Measures for Face Detection and Matching.
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David Lloret, Antonio Lopez, & Joan Serrat. (1998). Precise registration of CT and MR volumes based on a new creaseness measure.
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Antonio Lopez. (1997). Ridge/Valley-like structures: Creases, separatrices and drainage patterns.
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Bart M. Ter Haar Romeny, W. Niessen, J. Weickert, P. Van Roermund, W. Van Enk, Antonio Lopez, et al. (1996). Orientation detection of trabecular bone. In Biophysics and Molecular Biology, International Biophysics Congress. Volume 65, pgs. P–H5–43.
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David Lloret, Antonio Lopez, & Joan Serrat. (1997). Rigid Registration of CT and MR volumes based on Rothes creases. In (SNRFAI’97) 7th Spanish National Symposium on Pattern Recognition and Image Analysis (pp. 1–6).
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Debora Gil, & Petia Radeva. (2004). A Regularized Curvature Flow Designed for a Selective Shape Restoration. IEEE Transactions on Image Processing, 13, 1444–1458.
Abstract: Among all filtering techniques, those based exclu- sively on image level sets (geometric flows) have proven to be the less sensitive to the nature of noise and the most contrast preserving. A common feature to existent curvature flows is that they penalize high curvature, regardless of the curve regularity. This constitutes a major drawback since curvature extreme values are standard descriptors of the contour geometry. We argue that an operator designed with shape recovery purposes should include a term penalizing irregularity in the curvature rather than its magnitude. To this purpose, we present a novel geometric flow that includes a function that measures the degree of local irregularity present in the curve. A main advantage is that it achieves non-trivial steady states representing a smooth model of level curves in a noisy image. Performance of our approach is compared to classical filtering techniques in terms of quality in the restored image/shape and asymptotic behavior. We empirically prove that our approach is the technique that achieves the best compromise between image quality and evolution stabilization.
Keywords: Geometric flows, nonlinear filtering, shape recovery.
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