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Francesco Brughi, Debora Gil, Llorenç Badiella, Eva Jove Casabella, & Oriol Ramos Terrades. (2014). "Exploring the impact of inter-query variability on the performance of retrieval systems " In 11th International Conference on Image Analysis and Recognition (Vol. 8814, 413–420). Springer International Publishing.
Abstract: This paper introduces a framework for evaluating the performance of information retrieval systems. Current evaluation metrics provide an average score that does not consider performance variability across the query set. In this manner, conclusions lack of any statistical significance, yielding poor inference to cases outside the query set and possibly unfair comparisons. We propose to apply statistical methods in order to obtain a more informative measure for problems in which different query classes can be identified. In this context, we assess the performance variability on two levels: overall variability across the whole query set and specific query class-related variability. To this end, we estimate confidence bands for precision-recall curves, and we apply ANOVA in order to assess the significance of the performance across different query classes.
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Debora Gil, Aura Hernandez-Sabate, Mireia Burnat, Steven Jansen, & Jordi Martinez-Vilalta. (2009). "Structure-Preserving Smoothing of Biomedical Images " In 13th International Conference on Computer Analysis of Images and Patterns (Vol. 5702, pp. 427–434). Springer Berlin Heidelberg.
Abstract: Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood. In this contribution, we use differential geometry concepts to define a diffusion operator that restricts to image consistent level-sets. In this manner, the final state is a non-uniform intensity image presenting homogeneous inter-tissue transitions along anatomical structures, while smoothing intra-structure texture. Experiments on different types of medical images (magnetic resonance, computerized tomography) illustrate its benefit on a further process (such as segmentation) of images.
Keywords: non-linear smoothing; differential geometry; anatomical structures segmentation; cardiac magnetic resonance; computerized tomography.
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Patricia Marquez, Debora Gil, R.Mester, & Aura Hernandez-Sabate. (2014). "Local Analysis of Confidence Measures for Optical Flow Quality Evaluation " In 9th International Conference on Computer Vision Theory and Applications (Vol. 3, pp. 450–457).
Abstract: Optical Flow (OF) techniques facing the complexity of real sequences have been developed in the last years. Even using the most appropriate technique for our specific problem, at some points the output flow might fail to achieve the minimum error required for the system. Confidence measures computed from either input data or OF output should discard those points where OF is not accurate enough for its further use. It follows that evaluating the capabilities of a confidence measure for bounding OF error is as important as the definition
itself. In this paper we analyze different confidence measures and point out their advantages and limitations for their use in real world settings. We also explore the agreement with current tools for their evaluation of confidence measures performance.
Keywords: Optical Flow; Confidence Measure; Performance Evaluation.
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Aura Hernandez-Sabate, Debora Gil, David Roche, Monica M. S. Matsumoto, & Sergio S. Furuie. (2011). "Inferring the Performance of Medical Imaging Algorithms " In Pedro Real, Daniel Diaz-Pernil, Helena Molina-Abril, Ainhoa Berciano, & Walter Kropatsch (Eds.), 14th International Conference on Computer Analysis of Images and Patterns (Vol. 6854, pp. 520–528). L. Berlin: Springer-Verlag Berlin Heidelberg.
Abstract: Evaluation of the performance and limitations of medical imaging algorithms is essential to estimate their impact in social, economic or clinical aspects. However, validation of medical imaging techniques is a challenging task due to the variety of imaging and clinical problems involved, as well as, the difficulties for systematically extracting a reliable solely ground truth. Although specific validation protocols are reported in any medical imaging paper, there are still two major concerns: definition of standardized methodologies transversal to all problems and generalization of conclusions to the whole clinical data set.
We claim that both issues would be fully solved if we had a statistical model relating ground truth and the output of computational imaging techniques. Such a statistical model could conclude to what extent the algorithm behaves like the ground truth from the analysis of a sampling of the validation data set. We present a statistical inference framework reporting the agreement and describing the relationship of two quantities. We show its transversality by applying it to validation of two different tasks: contour segmentation and landmark correspondence.
Keywords: Validation, Statistical Inference, Medical Imaging Algorithms.
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David Roche, Debora Gil, & Jesus Giraldo. (2013). "Detecting loss of diversity for an efficient termination of EAs " In 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (pp. 561–566).
Abstract: Termination of Evolutionary Algorithms (EA) at its steady state so that useless iterations are not performed is a main point for its efficient application to black-box problems. Many EA algorithms evolve while there is still diversity in their population and, thus, they could be terminated by analyzing the behavior some measures of EA population diversity. This paper presents a numeric approximation to steady states that can be used to detect the moment EA population has lost its diversity for EA termination. Our condition has been applied to 3 EA paradigms based on diversity and a selection of functions
covering the properties most relevant for EA convergence.
Experiments show that our condition works regardless of the search space dimension and function landscape.
Keywords: EA termination; EA population diversity; EA steady state
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Patricia Marquez, Debora Gil, & Aura Hernandez-Sabate. (2013). "Evaluation of the Capabilities of Confidence Measures for Assessing Optical Flow Quality " In ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars (pp. 624–631).
Abstract: Assessing Optical Flow (OF) quality is essential for its further use in reliable decision support systems. The absence of ground truth in such situations leads to the computation of OF Confidence Measures (CM) obtained from either input or output data. A fair comparison across the capabilities of the different CM for bounding OF error is required in order to choose the best OF-CM pair for discarding points where OF computation is not reliable. This paper presents a statistical probabilistic framework for assessing the quality of a given CM. Our quality measure is given in terms of the percentage of pixels whose OF error bound can not be determined by CM values. We also provide statistical tools for the computation of CM values that ensures a given accuracy of the flow field.
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Debora Gil, Oriol Rodriguez, J. Mauri, & Petia Radeva. (2006)." Statistical descriptors of the Myocardial perfusion in angiographic images" In Proc. Computers in Cardiology (pp. 677–680).
Abstract: Restoration of coronary flow after primary percutaneous coronary intervention in acute myocardial infarction does not always correlate with adequate myocardial perfusion. Recently, coronary angiography has been used to assess microcirculation integrity (Myocardial BlushAnalysis, MBA). Although MBA correlates with patient prognosis there are few image processing methods addressing objective perfusion quantification. The goal of this work is to develop statistical descriptors of the myocardial dyeing pattern allowing objective assessment of myocardial perfusion. Experiments on healthy right coronary arteries show that our approach allows reliable measurements without any specific image acquisition protocol.
Keywords: Anisotropic processing; intravascular ultrasound (IVUS); vessel border segmentation; vessel structure classification.
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Aura Hernandez-Sabate, Debora Gil, J. Mauri, & Petia Radeva. (2006). "Reducing cardiac motion in IVUS sequences " In Proceeding of Computers in Cardiology (Vol. 33, pp. 685–688).
Abstract: Cardiac vessel displacement is a main artifact in IVUS sequences. It hinders visualization of the main structures in an appropriate orientation and alignment and affects extracting vessel measurements. In this paper, we present a novel approach for image sequence alignment based on spectral analysis, which removes rigid dynamics, preserving at the same time the vessel geometry. First, we suppress the translation by taking, for each frame, the center of mass of the image as origin of coordinates. In polar coordinates with such point as origin, the rotation appears as a horizontal displacement. The translation induces a phase shift in the Fourier coefficients of two consecutive polar images. We estimate the phase by adjusting a regression plane to the phases of the principal frequencies. Experiments show that the presented strategy suppress cardiac motion regardless of the acquisition device. 1.
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Antoni Gurgui, Debora Gil, & Enric Marti. (2015). "Laplacian Unitary Domain for Texture Morphing " In Proceedings of the 10th International Conference on Computer Vision Theory and Applications VISIGRAPP2015 (Vol. 1, pp. 693–699). SciTePress.
Abstract: Deformation of expressive textures is the gateway to realistic computer synthesis of expressions. By their good mathematical properties and flexible formulation on irregular meshes, most texture mappings rely on solutions to the Laplacian in the cartesian space. In the context of facial expression morphing, this approximation can be seen from the opposite point of view by neglecting the metric. In this paper, we use the properties of the Laplacian in manifolds to present a novel approach to warping expressive facial images in order to generate a morphing between them.
Keywords: Facial; metamorphosis;LaplacianMorphing
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Jaume Garcia, Debora Gil, A.Bajo, M.J.Ledesma-Carbayo, & C.SantaMarta. (2008). "Influence of the temporal resolution on the quantification of displacement fields in cardiac magnetic resonance tagged images " In Alan Murray (Ed.), Proc. Computers in Cardiology (Vol. 35, pp. 785–788).
Abstract: It is difficult to acquire tagged cardiac MR images with a high temporal and spatial resolution using clinical MR scanners. However, if such images are used for quantifying scores based on motion, it is essential a resolution as high as possible. This paper explores the influence of the temporal resolution of a tagged series on the quantification of myocardial dynamic parameters. To such purpose we have designed a SPAMM (Spatial Modulation of Magnetization) sequence allowing acquisition of sequences at simple and double temporal resolution. Sequences are processed to compute myocardial motion by an automatic technique based on the tracking of the harmonic phase of tagged images (the Harmonic Phase Flow, HPF). The results have been compared to manual tracking of myocardial tags. The error in displacement fields for double resolution sequences reduces 17%.
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