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Debora Gil, & Petia Radeva. (2003)." Curvature based Distance Maps" . Computer Vision Center.
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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, Petia Radeva, & Fernando Vilariño. (2003). "Anisotropic Contour Completion " In Proceedings of the IEEE International Conference on Image Processing (I-869). Barcelona, Spain.
Abstract: In this paper we introduce a novel application of the diffusion tensor for anisotropic image processing. The Anisotropic Contour Completion (ACC) we suggest consists in extending the characteristic function of the open curve by means of a degenerated diffusion tensor that prevents any diffusion in the normal direction. We show that ACC is equivalent to a dilation with a continuous elliptic structural element that takes into account the local orientation of the contours to be closed. Experiments on contours extracted from real images show that ACC produces shapes able to adapt to any curve in an active contour framework. 1.
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Debora Gil, Petia Radeva, & J. Mauri. (2002). "Ivus Segmentation Via a Regularized Curvature Flow " In X Congreso Anual de la Sociedad Española de Ingeniería Biomédica CASEIB 2002 (pp. 133–136). Saragossa, Espanya.
Abstract: Cardiac diseases are diagnosed and treated through a study of the morphology and dynamics of cardiac arteries. In- travascular Ultrasound (IVUS) imaging is of high interest to physicians since it provides both information. At the current state-of-the-art in image segmentation, a robust detection of the arterial lumen in IVUS demands manual intervention or ECG-gating. Manual intervention is a tedious and time consuming task that requires experienced observers, meanwhile ECG-gating is an acquisition technique not available in all clinical centers. We introduce a parametric algorithm that detects the arterial luminal border in in vivo sequences. The method consist in smoothing the sequences’ level surfaces under a regularized mean curvature flow that admits non-trivial steady states. The flow is based on a measure of the surface local smoothness that takes into account regularity of the surface curvature.
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Debora Gil, Petia Radeva, Jordi Saludes, & J. Mauri. (2000). "Automatic Segmentation of Artery Wall in Coronary IVUS Images: A Probabilistic Approach " In International Conference on Pattern Recognition (Vol. 4, pp. 352–355).
Abstract: Intravascular ultrasound images represent a unique tool to analyze the morphology of arteries and vessels (plaques, restenosis, etc). The poor quality of these images makes unsupervised segmentation based on traditional segmentation algorithms (such as edge or ridge/valley detection) fail to achieve the expected results. In this paper we present a probabilistic flexible template to separate different regions in the image. In particular, we use elliptic templates to model and detect the shape of the vessel inner wall in IVUS images. We present the results of successful segmentation obtained from patients undergoing stent treatment. A physician team has validated these results.
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Debora Gil, Petia Radeva, Jordi Saludes, & J. Mauri. (2000). "Automatic Segmentation of Artery Wall in Coronary IVUS Images: a Probabilistic Approach " In Proceedings of CIC’2000. Cambridge, Massachussets.
Abstract: Intravascular ultrasound images represent a unique tool to analyze the morphology of arteries and vessels (plaques, restenosis, etc). The poor quality of these images makes unsupervised segmentation based on traditional segmentation algorithms (such as edge or ridge/valley detection) fail to achieve the expected results. In this paper we present a probabilistic flexible template to separate different regions in the image. In particular, we use elliptic templates to model and detect the shape of the vessel inner wall in IVUS images. We present the results of successful segmentation obtained from patients undergoing stent treatment. A physician team has validated these results.
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Debora Gil, Rosa Maria Ortiz, Carles Sanchez, & Antoni Rosell. (2018). "Objective endoscopic measurements of central airway stenosis. A pilot study " . Respiration, 95, 63–69.
Abstract: Endoscopic estimation of the degree of stenosis in central airway obstruction is subjective and highly variable. Objective: To determine the benefits of using SENSA (System for Endoscopic Stenosis Assessment), an image-based computational software, for obtaining objective stenosis index (SI) measurements among a group of expert bronchoscopists and general pulmonologists. Methods: A total of 7 expert bronchoscopists and 7 general pulmonologists were enrolled to validate SENSA usage. The SI obtained by the physicians and by SENSA were compared with a reference SI to set their precision in SI computation. We used SENSA to efficiently obtain this reference SI in 11 selected cases of benign stenosis. A Web platform with three user-friendly microtasks was designed to gather the data. The users had to visually estimate the SI from videos with and without contours of the normal and the obstructed area provided by SENSA. The users were able to modify the SENSA contours to define the reference SI using morphometric bronchoscopy. Results: Visual SI estimation accuracy was associated with neither bronchoscopic experience (p = 0.71) nor the contours of the normal and the obstructed area provided by the system (p = 0.13). The precision of the SI by SENSA was 97.7% (95% CI: 92.4-103.7), which is significantly better than the precision of the SI by visual estimation (p < 0.001), with an improvement by at least 15%. Conclusion: SENSA provides objective SI measurements with a precision of up to 99.5%, which can be calculated from any bronchoscope using an affordable scalable interface. Providing normal and obstructed contours on bronchoscopic videos does not improve physicians' visual estimation of the SI.
Keywords: Bronchoscopy; Tracheal stenosis; Airway stenosis; Computer-assisted analysis
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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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Debora Gil, Sergio Vera, Agnes Borras, Albert Andaluz, & Miguel Angel Gonzalez Ballester. (2017). "Anatomical Medial Surfaces with Efficient Resolution of Branches Singularities " . Medical Image Analysis, 35, 390–402.
Abstract: Medial surfaces are powerful tools for shape description, but their use has been limited due to the sensibility existing methods to branching artifacts. Medial branching artifacts are associated to perturbations of the object boundary rather than to geometric features. Such instability is a main obstacle for a condent application in shape recognition and description. Medial branches correspond to singularities of the medial surface and, thus, they are problematic for existing morphological and energy-based algorithms. In this paper, we use algebraic geometry concepts in an energy-based approach to compute a medial surface presenting a stable branching topology. We also present an ecient GPU-CPU implementation using standard image processing tools. We show the method computational eciency and quality on a custom made synthetic database. Finally, we present some results on a medical imaging application for localization of abdominal pathologies.
Keywords: Medial Representations; Shape Recognition; Medial Branching Stability ; Singular Points
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Debora Gil, Agnes Borras, Ruth Aris, Mariano Vazquez, Pierre Lafortune, & Guillame Houzeaux. (2012). "What a difference in biomechanics cardiac fiber makes " In Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges (Vol. 7746, pp. 253–260). Springer Berlin Heidelberg.
Abstract: Computational simulations of the heart are a powerful tool for a comprehensive understanding of cardiac function and its intrinsic relationship with its muscular architecture. Cardiac biomechanical models require a vector field representing the orientation of cardiac fibers. A wrong orientation of the fibers can lead to a
non-realistic simulation of the heart functionality. In this paper we explore the impact of the fiber information on the simulated biomechanics of cardiac muscular anatomy. We have used the John Hopkins database to perform a biomechanical simulation using both a synthetic benchmark fiber distribution and the data obtained experimentally from DTI. Results illustrate how differences in fiber orientation affect heart deformation along cardiac cycle.
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