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Agnes Borras; Josep Llados |
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Corest: A measure of color and space stability to detect salient regions according to human criteria |
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2009 |
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5th International Conference on Computer Vision Theory and Applications |
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204-209 |
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Lisboa, Portugal |
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978-989-8111-69-2 |
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VISAPP |
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DAG @ dag @ BoL2009 |
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1225 |
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Author |
Debora Gil; Antonio Esteban Lansaque; Agnes Borras; Carles Sanchez |
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Title |
Enhancing virtual bronchoscopy with intra-operative data using a multi-objective GAN |
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Journal Article |
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2019 |
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International Journal of Computer Assisted Radiology and Surgery |
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IJCAR |
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7 |
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1 |
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This manuscript has been withdrawn by bioRxiv due to upload of an incorrect version of the manuscript by the authors. Therefore, this manuscript should not be cited as reference for this project. |
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IAM; 600.139; 600.145 |
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Admin @ si @ GEB2019 |
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3307 |
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Author |
Sergio Vera; Debora Gil; Agnes Borras; Marius George Linguraru; Miguel Angel Gonzalez Ballester |
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Title |
Geometric Steerable Medial Maps |
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Journal Article |
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Year |
2013 |
Publication |
Machine Vision and Applications |
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MVA |
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24 |
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6 |
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1255-1266 |
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Medial Representations ,Medial Manifolds Comparation , Surface , Reconstruction |
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In order to provide more intuitive and easily interpretable representations of complex shapes/organs, medial manifolds should reach a compromise between simplicity in geometry and capability for restoring the anatomy/shape of the organ/volume. Existing morphological 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 avoids degenerated medial axis segments. Second, we introduce a continuous operator for accurate and efficient computation of medial structures of arbitrary dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to syn- thetic shapes of known medial geometry. We also show its higher performance for medical imaging applications in terms of simplicity of medial structures and capability for reconstructing the anatomical volume. |
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Springer Berlin Heidelberg |
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Mubarak Shah |
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0932-8092 |
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IAM; 605.203; 600.060; 600.044 |
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IAM @ iam @ VGB2013 |
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2192 |
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Author |
Agnes Borras; Francesc Tous; Josep Llados; Maria Vanrell |
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Title |
High-Level Clothes Description Based on Color-Texture and Structural Features |
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Book Chapter |
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2003 |
Publication |
Lecture Notes in Computer Science |
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2652 |
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108–116 |
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This work is a part of a surveillance system where content- based image retrieval is done in terms of people appearance. Given an image of a person, our work provides an automatic description of his clothing according to the colour, texture and structural composition of its garments. We present a two-stage process composed by image segmentation and a region-based interpretation. We segment an image by modelling it due to an attributed graph and applying a hybrid method that follows a split-and-merge strategy. We propose the interpretation of five cloth combinations that are modelled in a graph structure in terms of region features. The interpretation is viewed as a graph matching with an associated cost between the segmentation and the cloth models. Fi- nally, we have tested the process with a ground-truth of one hundred images. |
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Springer-Verlag |
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DAG;CIC |
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CAT @ cat @ BTL2003a |
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368 |
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Author |
Agnes Borras; Francesc Tous; Josep Llados; Maria Vanrell |
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Title |
High-Level Clothes Description Based on Colour-Texture and Structural Features |
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Conference Article |
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2003 |
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1rst. Iberian Conference on Pattern Recognition and Image Analysis IbPRIA 2003 |
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Palma de Mallorca |
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DAG;CIC |
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CAT @ cat @ BTL2003b |
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369 |
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Author |
Agnes Borras |
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Title |
High-Level Clothes Description Based on Colour-Texture Features. |
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Miscellaneous |
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2002 |
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Director: J. Llados, Master Thesis. |
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DAG @ dag @ Bor2002 |
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322 |
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Author |
Esmitt Ramirez; Carles Sanchez; Agnes Borras; Marta Diez-Ferrer; Antoni Rosell; Debora Gil |
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Title |
Image-Based Bronchial Anatomy Codification for Biopsy Guiding in Video Bronchoscopy |
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Conference Article |
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2018 |
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OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, and Skin Image Analysis |
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11041 |
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Biopsy guiding; Bronchoscopy; Lung biopsy; Intervention guiding; Airway codification |
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Bronchoscopy examinations allow biopsy of pulmonary nodules with minimum risk for the patient. Even for experienced bronchoscopists, it is difficult to guide the bronchoscope to most distal lesions and obtain an accurate diagnosis. This paper presents an image-based codification of the bronchial anatomy for bronchoscopy biopsy guiding. The 3D anatomy of each patient is codified as a binary tree with nodes representing bronchial levels and edges labeled using their position on images projecting the 3D anatomy from a set of branching points. The paths from the root to leaves provide a codification of navigation routes with spatially consistent labels according to the anatomy observes in video bronchoscopy explorations. We evaluate our labeling approach as a guiding system in terms of the number of bronchial levels correctly codified, also in the number of labels-based instructions correctly supplied, using generalized mixed models and computer-generated data. Results obtained for three independent observers prove the consistency and reproducibility of our guiding system. We trust that our codification based on viewer’s projection might be used as a foundation for the navigation process in Virtual Bronchoscopy systems. |
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Granada; September 2018 |
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MICCAIW |
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IAM; 600.096; 600.075; 601.323; 600.145 |
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Admin @ si @ RSB2018b |
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3137 |
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Author |
Debora Gil; Ruth Aris; Agnes Borras; Esmitt Ramirez; Rafael Sebastian; Mariano Vazquez |
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Title |
Influence of fiber connectivity in simulations of cardiac biomechanics |
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Journal Article |
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Year |
2019 |
Publication |
International Journal of Computer Assisted Radiology and Surgery |
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IJCAR |
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14 |
Issue |
1 |
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63–72 |
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Cardiac electromechanical simulations; Diffusion tensor imaging; Fiber connectivity |
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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. |
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IAM; 600.096; 601.323; 600.139; 600.145 |
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Admin @ si @ GAB2019a |
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3133 |
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Author |
Debora Gil; Antonio Esteban Lansaque; Agnes Borras; Esmitt Ramirez; Carles Sanchez |
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Title |
Intraoperative Extraction of Airways Anatomy in VideoBronchoscopy |
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2020 |
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IEEE Access |
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ACCESS |
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8 |
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159696 - 159704 |
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A main bottleneck in bronchoscopic biopsy sampling is to efficiently reach the lesion navigating across bronchial levels. Any guidance system should be able to localize the scope position during the intervention with minimal costs and alteration of clinical protocols. With the final goal of an affordable image-based guidance, this work presents a novel strategy to extract and codify the anatomical structure of bronchi, as well as, the scope navigation path from videobronchoscopy. Experiments using interventional data show that our method accurately identifies the bronchial structure. Meanwhile, experiments using simulated data verify that the extracted navigation path matches the 3D route. |
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IAM; 600.139; 600.145 |
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Admin @ si @ GEB2020 |
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3467 |
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Debora Gil; Agnes Borras; Manuel Ballester; Francesc Carreras; Ruth Aris; Manuel Vazquez; Enric Marti; Ferran Poveda |
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Title |
MIOCARDIA: Integrating cardiac function and muscular architecture for a better diagnosis |
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2011 |
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14th International Symposium on Applied Sciences in Biomedical and Communication Technologies |
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Deep understanding of myocardial structure of the heart would unravel crucial knowledge for clinical and medical procedures. The MIOCARDIA project is a multidisciplinary project in cooperation with l'Hospital de la Santa Creu i de Sant Pau, Clinica la Creu Blanca and Barcelona Supercomputing Center. The ultimate goal of this project is defining a computational model of the myocardium. The model takes into account the deep interrelation between the anatomy and the mechanics of the heart. The paper explains the workflow of the MIOCARDIA project. It also introduces a multiresolution reconstruction technique based on DT-MRI streamlining for simplified global myocardial model generation. Our reconstructions can restore the most complex myocardial structures and provides evidences of a global helical organization. |
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Barcelona; Spain |
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Association for Computing Machinery |
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Barcelona, Spain |
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Association for Computing Machinery |
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english |
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english |
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978-1-4503-0913-4 |
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IAM @ iam @ GGB2011 |
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1691 |
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