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Josep Llados, Enric Marti, & Jaime Lopez-Krahe. (1999). "A Hough-based method for hatched pattern detection in maps and diagrams " In Proceeding of the Fifth Int. Conf. Document Analysis and Recognition ICDAR ’99 (pp. 479–482).
Abstract: A hatched area is characterized by a set of parallel straight lines placed at regular intervals. In this paper, a Hough-based schema is introduced to recognize hatched areas in technical documents from attributed graph structures representing the document once it has been vectorized. Defining a Hough-based transform from a graph instead of the raster image allows to drastically reduce the processing time and, second, to obtain more reliable results because straight lines have already been detected in the vectorization step. A second advantage of the proposed method is that no assumptions must be made a priori about the slope and frequency of hatching patterns, but they are computed in run time for each hatched area.
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Ernest Valveny, Ricardo Toledo, Ramon Baldrich, & Enric Marti. (2002)." Combining recognition-based in segmentation-based approaches for graphic symol recognition using deformable template matching" In Proceeding of the Second IASTED International Conference Visualization, Imaging and Image Proceesing VIIP 2002 (502–507).
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Gloria Fernandez Esparrach, Jorge Bernal, Cristina Rodriguez de Miguel, Debora Gil, Fernando Vilariño, Henry Cordova, et al. (2015). "Colonic polyps are correctly identified by a computer vision method using wm-dova energy maps " In Proceedings of 23 United European- UEG Week 2015.
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Debora Gil, Petia Radeva, Jordi Saludes, & Josefina 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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Petia Radeva, & Enric Marti. (1995). "An improved model of snakes for model-based segmentation " In Proceedings of Computer Analysis of Images and Patterns (pp. 515–520).
Abstract: The main advantage of segmentation by snakes consists in its ability to incorporate smoothness constraints on the detected shapes that can occur. Likewise, we propose to model snakes with other properties that reflect the information provided about the object of interest in a different extent. We consider different kinds of snakes, those searching for contours with a certain direction, those preserving an object’s model, those seeking for symmetry, those expanding open, etc. The availability of such a collection of snakes allows not only the more complete use of the knowledge about the segmented object, but also to solve some problems of the existing snakes. Our experiments on segmentation of facial features justify the usefulness of snakes with different properties.
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Gemma Sanchez, Ernest Valveny, Josep Llados, Enric Marti, Oriol Ramos Terrades, N.Lozano, et al. (2003)." A system for virtual prototyping of architectural projects" In Proceedings of Fifth IAPR International Workshop on Pattern Recognition (pp. 65–74).
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Cristina Cañero, Petia Radeva, Oriol Pujol, Ricardo Toledo, Debora Gil, J. Saludes, et al. (1999). "Optimal Stent Implantation: Three-dimensional Evaluation of the Mutual Position of Stent and Vessel via Intracoronary Ecography " In Proceedings of International Conference on Computer in Cardiology (CIC´99).
Abstract: We present a new automatic technique to visualize and quantify the mutual position between the stent and the vessel wall by considering their three-dimensional reconstruction. Two deformable generalized cylinders adapt to the image features in all IVUS planes corresponding to the vessel wall and the stent in order to reconstruct the boundaries of the stent and the vessel in space. The image features that characterize the stent and the vessel wall are determined in terms of edge and ridge image detectors taking into account the gray level of the image pixels. We show that the 30 reconstruction by deformable cylinders is accurate and robust due to the spatial data coherence in the considered volumetric IVUS image. The main clinic utility of the stent and vessel reconstruction by deformable’ cylinders consists of its possibility to visualize and to assess the optimal stent introduction.
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Cristina Cañero, Petia Radeva, Oriol Pujol, Ricardo Toledo, Debora Gil, J. Saludes, et al. (1999). "Three-dimensional reconstruction and quantification of the coronary tree using intravascular ultrasound images " In Proceedings of International Conference on Computer in Cardiology (CIC´99).
Abstract: In this paper we propose a new Computer Vision technique to reconstruct the vascular wall in space using a deformable model-based technique and compounding methods, based in biplane angiography and intravascular ultrasound data jicsion. It is also proposed a generalpurpose three-dimensional guided interpolation method. The three dimensional centerline of the vessel is reconstructed from geometrically corrected biplane angiographies using automatic segmentation methods and snakes. The IVUS image planes are located in the threedimensional space and correctly oriented. A led interpolation method based in B-SurJaces and snakes isused to fill the gaps among image planes
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Josep Llados, Ernest Valveny, Gemma Sanchez, & Enric Marti. (2003). A Case Study of Pattern Recognition: Symbol Recognition in Graphic Documentsa In Proceedings of Pattern Recognition in Information Systems (pp. 1–13). ICEIS Press.
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Paula Fritzsche, C.Roig, Ana Ripoll, Emilio Luque, & Aura Hernandez-Sabate. (2006). "A Performance Prediction Methodology for Data-dependent Parallel Applications " In Proceedings of the IEEE International Conference on Cluster Computing (pp. 1–8).
Abstract: The increase in the use of parallel distributed architectures in order to solve large-scale scientific problems has generated the need for performance prediction for both deterministic applications and non-deterministic applications. In particular, the performance prediction of data dependent programs is an extremely challenging problem because for a specific issue the input datasets may cause different execution times. Generally, a parallel application is characterized as a collection of tasks and their interrelations. If the application is time-critical it is not enough to work with only one value per task, and consequently knowledge of the distribution of task execution times is crucial. The development of a new prediction methodology to estimate the performance of data-dependent parallel applications is the primary target of this study. This approach makes it possible to evaluate the parallel performance of an application without the need of implementation. A real data-dependent arterial structure detection application model is used to apply the methodology proposed. The predicted times obtained using the new methodology for genuine datasets are compared with predicted times that arise from using only one execution value per task. Finally, the experimental study shows that the new methodology generates more precise predictions.
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