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Jaume Garcia, Debora Gil, Francesc Carreras, Sandra Pujades, & R.Leta. (2007). "Modelització 4-Dimensional de la Funció Siatólica del Ventricle Esquerre " In XIX Congrés de la Societat Catalana de Cardiologia de Barcelona (pp. 133–134). Barcelona (Spain).
Abstract: L’evolució tecnològica en el tractament de les imatges mèdiques permet reconstruir, amb el software apropiat, imatges tridimensionals de les estructures cardiovasculars i dotar-les de moviment. Les imatges 4D resultants faciliten l’estudi de la fisiopatologia de la insuficiència cardíaca en base als transtorns de l’activació electromecànica ventricular, el que pot ser d’interès en el procés de selecció de pacients candidats a teràpies de resincronització. Presentem els resultats preliminars de la reconstrucció 4D del ventricle esquerre (VE) a partir de les seqüències de tagging miocàrdic del VE.
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Debora Gil, Petia Radeva, & Josefina 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, Oriol Ramos Terrades, Elisa Minchole, Carles Sanchez, Noelia Cubero de Frutos, Marta Diez-Ferrer, et al. (2017). "Classification of Confocal Endomicroscopy Patterns for Diagnosis of Lung Cancer " In 6th Workshop on Clinical Image-based Procedures: Translational Research in Medical Imaging (Vol. 10550, pp. 151–159).
Abstract: Confocal Laser Endomicroscopy (CLE) is an emerging imaging technique that allows the in-vivo acquisition of cell patterns of potentially malignant lesions. Such patterns could discriminate between inflammatory and neoplastic lesions and, thus, serve as a first in-vivo biopsy to discard cases that do not actually require a cell biopsy.
The goal of this work is to explore whether CLE images obtained during videobronchoscopy contain enough visual information to discriminate between benign and malign peripheral lesions for lung cancer diagnosis. To do so, we have performed a pilot comparative study with 12 patients (6 adenocarcinoma and 6 benign-inflammatory) using 2 different methods for CLE pattern analysis: visual analysis by 3 experts and a novel methodology that uses graph methods to find patterns in pre-trained feature spaces. Our preliminary results indicate that although visual analysis can only achieve a 60.2% of accuracy, the accuracy of the proposed unsupervised image pattern classification raises to 84.6%.
We conclude that CLE images visual information allow in-vivo detection of neoplastic lesions and graph structural analysis applied to deep-learning feature spaces can achieve competitive results.
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Carles Sanchez, Debora Gil, Antoni Rosell, Albert Andaluz, & F. Javier Sanchez. (2013). "Segmentation of Tracheal Rings in Videobronchoscopy combining Geometry and Appearance " In Sebastiano Battiato and José Braz (Ed.), Proceedings of the International Conference on Computer Vision Theory and Applications (Vol. 1, pp. 153–161). Portugal: SciTePress.
Abstract: Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways and minimal invasive interventions. Tracheal procedures are ordinary interventions that require measurement of the percentage of obstructed pathway for injury (stenosis) assessment. Visual assessment of stenosis in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error. Accurate detection of tracheal rings is the basis for automated estimation of the size of stenosed trachea. Processing of videobronchoscopic images acquired at the operating room is a challenging task due to the wide range of artifacts and acquisition conditions. We present a model of the geometric-appearance of tracheal rings for its detection in videobronchoscopic videos. Experiments on sequences acquired at the operating room, show a performance close to inter-observer variability
Keywords: Video-bronchoscopy, tracheal ring segmentation, trachea geometric and appearance model
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Debora Gil, Antonio Esteban Lansaque, Sebastian Stefaniga, Mihail Gaianu, & Carles Sanchez. (2019). "Data Augmentation from Sketch " In International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging (Vol. 11840, pp. 155–162).
Abstract: State of the art machine learning methods need huge amounts of data with unambiguous annotations for their training. In the context of medical imaging this is, in general, a very difficult task due to limited access to clinical data, the time required for manual annotations and variability across experts. Simulated data could serve for data augmentation provided that its appearance was comparable to the actual appearance of intra-operative acquisitions. Generative Adversarial Networks (GANs) are a powerful tool for artistic style transfer, but lack a criteria for selecting epochs ensuring also preservation of intra-operative content.
We propose a multi-objective optimization strategy for a selection of cycleGAN epochs ensuring a mapping between virtual images and the intra-operative domain preserving anatomical content. Our approach has been applied to simulate intra-operative bronchoscopic videos and chest CT scans from virtual sketches generated using simple graphical primitives.
Keywords: Data augmentation; cycleGANs; Multi-objective optimization
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Antoni Gurgui, Debora Gil, Enric Marti, & Vicente Grau. (2016). "Left-Ventricle Basal Region Constrained Parametric Mapping to Unitary Domain " In 7th International Workshop on Statistical Atlases & Computational Modelling of the Heart (Vol. 10124, pp. 163–171).
Abstract: Due to its complex geometry, the basal ring is often omitted when putting different heart geometries into correspondence. In this paper, we present the first results on a new mapping of the left ventricle basal rings onto a normalized coordinate system using a fold-over free approach to the solution to the Laplacian. To guarantee correspondences between different basal rings, we imposed some internal constrained positions at anatomical landmarks in the normalized coordinate system. To prevent internal fold-overs, constraints are handled by cutting the volume into regions defined by anatomical features and mapping each piece of the volume separately. Initial results presented in this paper indicate that our method is able to handle internal constrains without introducing fold-overs and thus guarantees one-to-one mappings between different basal ring geometries.
Keywords: Laplacian; Constrained maps; Parameterization; Basal ring
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Josep Llados, Horst Bunke, & Enric Marti. (1997). Using Cyclic String Matching to Find Rotational and Reflectional Symmetries in Shapes In Intelligent Robots: Sensing, Modeling and Planning (pp. 164–179). World Scientific Press.
Abstract: Dagstuhl Workshop
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Jaume Garcia, David Rotger, Francesc Carreras, R.Leta, & Petia Radeva. (2003). "Contrast echography segmentation and tracking by trained deformable models " In Proc. Computers in Cardiology (Vol. 30, pp. 173–176). Centre de Visió per Computador – Dept. Informàtica, UAB Edifici O – Campus UAB, 08193 Bellater.
Abstract: The objective of this work is to segment the human left ventricle myocardium (LVM) in contrast echocardiography imaging and thus track it along a cardiac cycle in order to extract quantitative data about heart function. Ultrasound images are hard to work with due to their speckle appearance. To overcome this we report the combination of active contour models (ACM) or snakes and active shape models (ASM). The ability of ACM in giving closed and smooth curves in addition to the power of the ASM in producing shapes similar to the ones learned, evoke to a robust algorithm. Meanwhile the snake is attracted towards image main features, ASM acts as a correction factor. The algorithm was tested independently on 180 frames and satisfying results were obtained: in 95% the maximum difference between automatic and experts segmentation was less than 12 pixels.
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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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Petia Radeva, A.Amini, J.Huang, & Enric Marti. (1996). "Deformable B-Solids and Implicit Snakes for Localization and Tracking of SPAMM MRI-Data " In Workshop on Mathematical Methods in Biomedical Image Analysis (pp. 192–201). IEEE Computer Society.
Abstract: To date, MRI-SPAMM data from different image slices have been analyzed independently. In this paper, we propose an approach for 3D tag localization and tracking of SPAMM data by a novel deformable B-solid. The solid is defined in terms of a 3D tensor product B-spline. The isoparametric curves of the B-spline solid have special importance. These are termed implicit snakes as they deform under image forces from tag lines in different image slices. The localization and tracking of tag lines is performed under constraints of continuity and smoothness of the B-solid. The framework unifies the problems of localization, and displacement fitting and interpolation into the same procedure utilizing B-spline bases for interpolation. To track motion from boundaries and restrict image forces to the myocardium, a volumetric model is employed as a pair of coupled endocardial and epicardial B-spline surfaces. To recover deformations in the LV an energy-minimization problem is posed where both tag and ...
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