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Debora Gil, Jordi Gonzalez, & Gemma Sanchez (Eds.). (2007)." Computer Vision: Advances in Research and Development" . 2. Bellaterra (Spain): UAB.
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Enric Marti, Debora Gil, & Carme Julia. (2008)." Experiencia d aplicació de la metodología d aprenentatge per proyectes en assignatures d Enginyeria Informàtica per a una millor adaptació als crèdits ECTS i EEES" (IDES-UAB, & E. A. M.Enric Martinez, Eds.) (Vol. 1). UAB.
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Debora Gil, Oriol Rodriguez-Leon, Petia Radeva, & Aura Hernandez-Sabate. (2007). "Assessing Artery Motion Compensation in IVUS " In Computer Analysis Of Images And Patterns (Vol. 4673, pp. 213–220). Lecture Notes in Computer Science. Heidelberg: Springerlink.
Abstract: Cardiac dynamics suppression is a main issue for visual improvement and computation of tissue mechanical properties in IntraVascular UltraSound (IVUS). Although in recent times several motion compensation techniques have arisen, there is a lack of objective evaluation of motion reduction in in vivo pullbacks. We consider that the assessment protocol deserves special attention for the sake of a clinical applicability as reliable as possible. Our work focuses on defining a quality measure and a validation protocol assessing IVUS motion compensation. On the grounds of continuum mechanics laws we introduce a novel score measuring motion reduction in in vivo sequences. Synthetic experiments validate the proposed score as measure of motion parameters accuracy; while results in in vivo pullbacks show its reliability in clinical cases.
Keywords: validation standards; quality measures; IVUS motion compensation; conservation laws; Fourier development
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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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Patricia Marquez, Debora Gil, & Aura Hernandez-Sabate. (2012). "Error Analysis for Lucas-Kanade Based Schemes " In 9th International Conference on Image Analysis and Recognition (Vol. 7324, pp. 184–191). Lecture Notes in Computer Science. Springer-Verlag Berlin Heidelberg.
Abstract: Optical flow is a valuable tool for motion analysis in medical imaging sequences. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in medical sequences. This paper presents an error analysis of Lucas-Kanade schemes in terms of intrinsic design errors and numerical stability of the algorithm. Our analysis provides a confidence measure that is naturally correlated to the accuracy of the flow field. Our experiments show the higher predictive value of our confidence measure compared to existing measures.
Keywords: Optical flow, Confidence measure, Lucas-Kanade, Cardiac Magnetic Resonance
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Patricia Marquez, Debora Gil, & Aura Hernandez-Sabate. (2012). "A Complete Confidence Framework for Optical Flow " In Rita Cucchiara V. M. Andrea Fusiello (Ed.), 12th European Conference on Computer Vision – Workshops and Demonstrations (Vol. 7584, pp. 124–133). Florence, Italy, October 7-13, 2012: Springer-Verlag.
Abstract: Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs, exploring the use of medial manifolds for the representation of multi-organ relations.
Keywords: Optical flow, confidence measures, sparsification plots, error prediction plots
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Debora Gil, & Petia Radeva. (2003). "Curvature Vector Flow to Assure Convergent Deformable Models for Shape Modelling " In B. Springer (Ed.), Energy Minimization Methods In Computer Vision And Pattern Recognition (Vol. 2683, pp. 357–372). Lecture Notes in Computer Science. Lisbon, PORTUGAL: Springer, Berlin.
Abstract: Poor convergence to concave shapes is a main limitation of snakes as a standard segmentation and shape modelling technique. The gradient of the external energy of the snake represents a force that pushes the snake into concave regions, as its internal energy increases when new inexion points are created. In spite of the improvement of the external energy by the gradient vector ow technique, highly non convex shapes can not be obtained, yet. In the present paper, we develop a new external energy based on the geometry of the curve to be modelled. By tracking back the deformation of a curve that evolves by minimum curvature ow, we construct a distance map that encapsulates the natural way of adapting to non convex shapes. The gradient of this map, which we call curvature vector ow (CVF), is capable of attracting a snake towards any contour, whatever its geometry. Our experiments show that, any initial snake condition converges to the curve to be modelled in optimal time.
Keywords: Initial condition; Convex shape; Non convex analysis; Increase; Segmentation; Gradient; Standard; Standards; Concave shape; Flow models; Tracking; Edge detection; Curvature
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Debora Gil, David Roche, Agnes Borras, & Jesus Giraldo. (2015). "Terminating Evolutionary Algorithms at their Steady State " . Computational Optimization and Applications, 61(2), 489–515.
Abstract: Assessing the reliability of termination conditions for evolutionary algorithms (EAs) is of prime importance. An erroneous or weak stop criterion can negatively affect both the computational effort and the final result. We introduce a statistical framework for assessing whether a termination condition is able to stop an EA at its steady state, so that its results can not be improved anymore. We use a regression model in order to determine the requirements ensuring that a measure derived from EA evolving population is related to the distance to the optimum in decision variable space. Our framework is analyzed across 24 benchmark test functions and two standard termination criteria based on function fitness value in objective function space and EA population decision variable space distribution for the differential evolution (DE) paradigm. Results validate our framework as a powerful tool for determining the capability of a measure for terminating EA and the results also identify the decision variable space distribution as the best-suited for accurately terminating DE in real-world applications.
Keywords: Evolutionary algorithms; Termination condition; Steady state; Differential evolution
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Francesc Carreras, Jaume Garcia, Debora Gil, Sandra Pujadas, Chi ho Lion, R.Suarez-Arias, et al. (2012). "Left ventricular torsion and longitudinal shortening: two fundamental components of myocardial mechanics assessed by tagged cine-MRI in normal subjects " . International Journal of Cardiovascular Imaging, 28(2), 273–284.
Abstract: Cardiac magnetic resonance imaging (Cardiac MRI) has become a gold standard diagnostic technique for the assessment of cardiac mechanics, allowing the non-invasive calculation of left ventric- ular long axis longitudinal shortening (LVLS) and absolute myocardial torsion (AMT) between basal and apical left ventricular slices, a movement directly related to the helicoidal anatomic disposition of the myocardial fibers. The aim of this study is to determine AMT and LVLS behaviour and normal values from a group of healthy subjects. A group of 21 healthy volunteers (15 males) (age: 23–55 y.o., mean:30.7 ± 7.5) were prospectively included in an obser- vational study by Cardiac MRI. Left ventricular rotation (degrees) was calculated by custom-made software (Harmonic Phase Flow) in consecutive LV short axis planes tagged cine-MRI sequences. AMT was determined from the difference between basal and apical planes LV rotations. LVLS (%) was determined from the LV longitudinal and horizontal axis cine-MRI images. All the 21 cases studied were interpretable, although in three cases the value of the LV apical rotation could not be determined. The mean rotation of the basal and apical planes at end-systole were -3.71° ± 0.84° and 6.73° ± 1.69° (n:18) respectively, resulting in a LV mean AMT of 10.48° ± 1.63° (n:18). End-systolic mean LVLS was 19.07 ± 2.71%. Cardiac MRI allows for the calculation of AMT and LVLS, fundamental functional components of the ventricular twist mechanics conditioned, in turn, by the anatomical helical layout of the myocardial fibers. These values provide complementary information about systolic ventricular function in relation to the traditional parameters used in daily practice.
Keywords: Magnetic resonance imaging (MRI); Tagging MRI; Cardiac mechanics; Ventricular torsion
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David Roche, Debora Gil, & Jesus Giraldo. (2014). "Mathematical modeling of G protein-coupled receptor function: What can we learn from empirical and mechanistic models? " In G Protein-Coupled Receptors – Modeling and Simulation Advances in Experimental Medicine and Biology (Vol. 796, pp. 159–181). Springer Netherlands.
Abstract: Empirical and mechanistic models differ in their approaches to the analysis of pharmacological effect. Whereas the parameters of the former are not physical constants those of the latter embody the nature, often complex, of biology. Empirical models are exclusively used for curve fitting, merely to characterize the shape of the E/[A] curves. Mechanistic models, on the contrary, enable the examination of mechanistic hypotheses by parameter simulation. Regretfully, the many parameters that mechanistic models may include can represent a great difficulty for curve fitting, representing, thus, a challenge for computational method development. In the present study some empirical and mechanistic models are shown and the connections, which may appear in a number of cases between them, are analyzed from the curves they yield. It may be concluded that systematic and careful curve shape analysis can be extremely useful for the understanding of receptor function, ligand classification and drug discovery, thus providing a common language for the communication between pharmacologists and medicinal chemists.
Keywords: β-arrestin; biased agonism; curve fitting; empirical modeling; evolutionary algorithm; functional selectivity; G protein; GPCR; Hill coefficient; intrinsic efficacy; inverse agonism; mathematical modeling; mechanistic modeling; operational model; parameter optimization; receptor dimer; receptor oligomerization; receptor constitutive activity; signal transduction; two-state model
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