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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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Jorge Bernal, F. Javier Sanchez, Gloria Fernandez Esparrach, Debora Gil, Cristina Rodriguez de Miguel, & Fernando Vilariño. (2015). "WM-DOVA Maps for Accurate Polyp Highlighting in Colonoscopy: Validation vs. Saliency Maps from Physicians " . Computerized Medical Imaging and Graphics, 43, 99–111.
Abstract: We introduce in this paper a novel polyp localization method for colonoscopy videos. Our method is based on a model of appearance for polyps which defines polyp boundaries in terms of valley information. We propose the integration of valley information in a robust way fostering complete, concave and continuous boundaries typically associated to polyps. This integration is done by using a window of radial sectors which accumulate valley information to create WMDOVA1 energy maps related with the likelihood of polyp presence. We perform a double validation of our maps, which include the introduction of two new databases, including the first, up to our knowledge, fully annotated database with clinical metadata associated. First we assess that the highest value corresponds with the location of the polyp in the image. Second, we show that WM-DOVA energy maps can be comparable with saliency maps obtained from physicians' fixations obtained via an eye-tracker. Finally, we prove that our method outperforms state-of-the-art computational saliency results. Our method shows good performance, particularly for small polyps which are reported to be the main sources of polyp miss-rate, which indicates the potential applicability of our method in clinical practice.
Keywords: Polyp localization; Energy Maps; Colonoscopy; Saliency; Valley detection
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Juan Borrego-Carazo, Carles Sanchez, David Castells, Jordi Carrabina, & Debora Gil. (2023). "BronchoPose: an analysis of data and model configuration for vision-based bronchoscopy pose estimation " . Computer Methods and Programs in Biomedicine, 228, 107241.
Abstract: Vision-based bronchoscopy (VB) models require the registration of the virtual lung model with the frames from the video bronchoscopy to provide effective guidance during the biopsy. The registration can be achieved by either tracking the position and orientation of the bronchoscopy camera or by calibrating its deviation from the pose (position and orientation) simulated in the virtual lung model. Recent advances in neural networks and temporal image processing have provided new opportunities for guided bronchoscopy. However, such progress has been hindered by the lack of comparative experimental conditions.
In the present paper, we share a novel synthetic dataset allowing for a fair comparison of methods. Moreover, this paper investigates several neural network architectures for the learning of temporal information at different levels of subject personalization. In order to improve orientation measurement, we also present a standardized comparison framework and a novel metric for camera orientation learning. Results on the dataset show that the proposed metric and architectures, as well as the standardized conditions, provide notable improvements to current state-of-the-art camera pose estimation in video bronchoscopy.
Keywords: Videobronchoscopy guiding; Deep learning; Architecture optimization; Datasets; Standardized evaluation framework; Pose estimation
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Oriol Ramos Terrades, Albert Berenguel, & Debora Gil. (2022). "A Flexible Outlier Detector Based on a Topology Given by Graph Communities " . Big Data Research, 29, 100332.
Abstract: Outlier detection is essential for optimal performance of machine learning methods and statistical predictive models. Their detection is especially determinant in small sample size unbalanced problems, since in such settings outliers become highly influential and significantly bias models. This particular experimental settings are usual in medical applications, like diagnosis of rare pathologies, outcome of experimental personalized treatments or pandemic emergencies. In contrast to population-based methods, neighborhood based local approaches compute an outlier score from the neighbors of each sample, are simple flexible methods that have the potential to perform well in small sample size unbalanced problems. A main concern of local approaches is the impact that the computation of each sample neighborhood has on the method performance. Most approaches use a distance in the feature space to define a single neighborhood that requires careful selection of several parameters, like the number of neighbors.
This work presents a local approach based on a local measure of the heterogeneity of sample labels in the feature space considered as a topological manifold. Topology is computed using the communities of a weighted graph codifying mutual nearest neighbors in the feature space. This way, we provide with a set of multiple neighborhoods able to describe the structure of complex spaces without parameter fine tuning. The extensive experiments on real-world and synthetic data sets show that our approach outperforms, both, local and global strategies in multi and single view settings.
Keywords: Classification algorithms; Detection algorithms; Description of feature space local structure; Graph communities; Machine learning algorithms; Outlier detectors
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Debora Gil, Ruth Aris, Agnes Borras, Esmitt Ramirez, Rafael Sebastian, & Mariano Vazquez. (2019). "Influence of fiber connectivity in simulations of cardiac biomechanics " . International Journal of Computer Assisted Radiology and Surgery, 14(1), 63–72.
Abstract: PURPOSE:
Personalized computational simulations of the heart could open up new improved approaches to diagnosis and surgery assistance systems. While it is fully recognized that myocardial fiber orientation is central for the construction of realistic computational models of cardiac electromechanics, the role of its overall architecture and connectivity remains unclear. Morphological studies show that the distribution of cardiac muscular fibers at the basal ring connects epicardium and endocardium. However, computational models simplify their distribution and disregard the basal loop. This work explores the influence in computational simulations of fiber distribution at different short-axis cuts.
METHODS:
We have used a highly parallelized computational solver to test different fiber models of ventricular muscular connectivity. We have considered two rule-based mathematical models and an own-designed method preserving basal connectivity as observed in experimental data. Simulated cardiac functional scores (rotation, torsion and longitudinal shortening) were compared to experimental healthy ranges using generalized models (rotation) and Mahalanobis distances (shortening, torsion).
RESULTS:
The probability of rotation was significantly lower for ruled-based models [95% CI (0.13, 0.20)] in comparison with experimental data [95% CI (0.23, 0.31)]. The Mahalanobis distance for experimental data was in the edge of the region enclosing 99% of the healthy population.
CONCLUSIONS:
Cardiac electromechanical simulations of the heart with fibers extracted from experimental data produce functional scores closer to healthy ranges than rule-based models disregarding architecture connectivity.
Keywords: Cardiac electromechanical simulations; Diffusion tensor imaging; Fiber connectivity
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Carles Sanchez, Jorge Bernal, F. Javier Sanchez, Antoni Rosell, Marta Diez-Ferrer, & Debora Gil. (2015). "Towards On-line Quantification of Tracheal Stenosis from Videobronchoscopy " . International Journal of Computer Assisted Radiology and Surgery, 10(6), 935–945.
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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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Mireia Sole, Joan Blanco, Debora Gil, Oliver Valero, B. Cardenas, G. Fonseka, et al. (2022). "Time to match; when do homologous chromosomes become closer? " Chromosoma, .
Abstract: In most eukaryotes, pairing of homologous chromosomes is an essential feature of meiosis that ensures homologous recombination and segregation. However, when the pairing process begins, it is still under investigation. Contrasting data exists in Mus musculus, since both leptotene DSB-dependent and preleptotene DSB-independent mechanisms have been described. To unravel this contention, we examined homologous pairing in pre-meiotic and meiotic Mus musculus cells using a threedimensional fuorescence in situ hybridization-based protocol, which enables the analysis of the entire karyotype using DNA painting probes. Our data establishes in an unambiguously manner that 73.83% of homologous chromosomes are already paired at premeiotic stages (spermatogonia-early preleptotene spermatocytes). The percentage of paired homologous chromosomes increases to 84.60% at mid-preleptotene-zygotene stage, reaching 100% at pachytene stage. Importantly, our results demonstrate a high percentage of homologous pairing observed before the onset of meiosis; this pairing does not occur randomly, as the percentage was higher than that observed in somatic cells (19.47%) and between nonhomologous chromosomes (41.1%). Finally, we have also observed that premeiotic homologous pairing is asynchronous and independent of the chromosome size, GC content, or presence of NOR regions.
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Ole Larsen, Petia Radeva, & Enric Marti. (1995). "Bounds on the optimal elasticity parameters for a snake " . Image Analysis and Processing, , 37–42.
Abstract: This paper develops a formalism by which an estimate for the upper and lower bounds for the elasticity parameters for a snake can be obtained. Objects different in size and shape give rise to different bounds. The bounds can be obtained based on an analysis of the shape of the object of interest. Experiments on synthetic images show a good correlation between the estimated behaviour of the snake and the one actually observed. Experiments on real X-ray images show that the parameters for optimal segmentation lie within the estimated bounds.
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