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Author |
Gemma Sanchez; Josep Llados; Enric Marti |
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Title |
A string-based method to recognize symbols and structural textures in architectural plans |
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1997 |
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2nd IAPR Workshop on Graphics Recognition |
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This paper deals with the recognition of symbols and struc- tural textures in architectural plans using string matching techniques. A plan is represented by an attributed graph whose nodes represent characteristic points and whose edges represent segments. Symbols and textures can be seen as a set of regions, i.e. closed loops in the graph, with a particular arrangement. The search for a symbol involves a graph matching between the regions of a model graph and the regions of the graph representing the document. Discriminating a texture means a clus- tering of neighbouring regions of this graph. Both procedures involve a similarity measure between graph regions. A string codification is used to represent the sequence of outlining edges of a region. Thus, the simila- rity between two regions is defined in terms of the string edit distance between their boundary strings. The use of string matching allows the recognition method to work also under presence of distortion. |
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Nancy, France |
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DAG; IAM |
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IAM @ iam @ SLE1997 |
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1498 |
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Author |
Jaume Garcia; Albert Andaluz; Debora Gil; Francesc Carreras |
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Title |
Decoupled External Forces in a Predictor-Corrector Segmentation Scheme for LV Contours in Tagged MR Images |
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Conference Article |
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2010 |
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32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
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4805-4808 |
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Computation of functional regional scores requires proper identification of LV contours. On one hand, manual segmentation is robust, but it is time consuming and requires high expertise. On the other hand, the tag pattern in TMR sequences is a problem for automatic segmentation of LV boundaries. We propose a segmentation method based on a predictorcorrector (Active Contours – Shape Models) scheme. Special stress is put in the definition of the AC external forces. First, we introduce a semantic description of the LV that discriminates myocardial tissue by using texture and motion descriptors. Second, in order to ensure convergence regardless of the initial contour, the external energy is decoupled according to the orientation of the edges in the image potential. We have validated the model in terms of error in segmented contours and accuracy of regional clinical scores. |
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Buenos Aires (Argentina) |
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IEEE EMB |
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1557-170X |
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978-1-4244-4123-5 |
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EMBC |
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IAM @ iam @ GAG2010 |
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1514 |
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Author |
Debora Gil; Guillermo Torres |
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Title |
A multi-shape loss function with adaptive class balancing for the segmentation of lung structures |
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2020 |
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34th International Congress and Exhibition on Computer Assisted Radiology & Surgery |
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Virtual; June 2020 |
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CARS |
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IAM; 600.139; 600.145 |
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Admin @ si @ GiT2020 |
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3472 |
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Author |
Guillermo Torres; Debora Gil; Antoni Rosell; S. Mena; Carles Sanchez |
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Title |
Virtual Radiomics Biopsy for the Histological Diagnosis of Pulmonary Nodules |
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2023 |
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37th International Congress and Exhibition is organized by Computer Assisted Radiology and Surgery |
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Pòster |
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Munich; Germany; June 2023 |
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CARS |
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Admin @ si @ TGR2023a |
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3950 |
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Author |
Carles Sanchez; Debora Gil; R. Tazi; Jorge Bernal; Y. Ruiz; L. Planas; F. Javier Sanchez; Antoni Rosell |
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Quasi-real time digital assessment of Central Airway Obstruction |
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2015 |
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3rd European congress for bronchology and interventional pulmonology ECBIP2015 |
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Barcelona; Spain; April 2015 |
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ECBIP |
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IAM; MV; 600.075 |
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SGT2015 |
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2612 |
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Author |
Debora Gil; Aura Hernandez-Sabate; Antoni Carol; Oriol Rodriguez; Petia Radeva |
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Title |
A Deterministic-Statistic Adventitia Detection in IVUS Images |
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Conference Article |
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2005 |
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3rd International workshop on International Workshop on Functional Imaging and Modeling of the Heart |
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65-74 |
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Electron microscopy; Unbending; 2D crystal; Interpolation; Approximation |
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Plaque analysis in IVUS planes needs accurate intima and adventitia models. Large variety in adventitia descriptors difficulties its detection and motivates using a classification strategy for selecting points on the structure. Whatever the set of descriptors used, the selection stage suffers from fake responses due to noise and uncompleted true curves. In order to smooth background noise while strengthening responses, we apply a restricted anisotropic filter that homogenizes grey levels along the image significant structures. Candidate points are extracted by means of a simple semi supervised adaptive classification of the filtered image response to edge and calcium detectors. The final model is obtained by interpolating the former line segments with an anisotropic contour closing technique based on functional extension principles. |
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Barcelona; June 2005 |
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FIMH |
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IAM;MILAB |
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IAM @ iam @ RMF2005 |
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1524 |
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Mireia Sole; Joan Blanco; Debora Gil; G. Fonseka; Richard Frodsham; Oliver Valero; Francesca Vidal; Zaida Sarrate |
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Is there a pattern of Chromosome territoriality along mice spermatogenesis? |
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Conference Article |
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2017 |
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3rd Spanish MeioNet Meeting Abstract Book |
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55-56 |
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Miraflores de la Sierra; Madrid; June 2017 |
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MEIONET |
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IAM; 600.096; 600.145 |
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Admin @ si @ |
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2958 |
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David Roche; Debora Gil; Jesus Giraldo |
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Assessing agonist efficacy in an uncertain Em world |
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Conference Article |
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2012 |
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40th Keystone Symposia on mollecular and celular biology |
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79 |
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The operational model of agonism has been widely used for the analysis of agonist action since its formulation in 1983. The model includes the Em parameter, which is defined as the maximum response of the system. The methods for Em estimation provide Em values not significantly higher than the maximum responses achieved by full agonists. However, it has been found that that some classes of compounds as, for instance, superagonists and positive allosteric modulators can increase the full agonist maximum response, implying upper limits for Em and thereby posing doubts on the validity of Em estimates. Because of the correlation between Em and operational efficacy, τ, wrong Em estimates will yield wrong τ estimates.
In this presentation, the operational model of agonism and various methods for the simulation of allosteric modulation will be analyzed. Alternatives for curve fitting will be presented and discussed. |
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Fairmont Banff Springs, Banff, Alberta, Canada |
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Keystone Symposia |
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Keystone Symposia |
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A. Christopoulus and M. Bouvier |
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english |
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english |
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Keystone Symposia |
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KSMCB |
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IAM @ iam @ RGG2012 |
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1855 |
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Marta Ligero; Guillermo Torres; Carles Sanchez; Katerine Diaz; Raquel Perez; Debora Gil |
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Title |
Selection of Radiomics Features based on their Reproducibility |
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2019 |
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41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
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403-408 |
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Dimensionality reduction is key to alleviate machine learning artifacts in clinical applications with Small Sample Size (SSS) unbalanced datasets. Existing methods rely on either the probabilistic distribution of training data or the discriminant power of the reduced space, disregarding the impact of repeatability and uncertainty in features.In the present study is proposed the use of reproducibility of radiomics features to select features with high inter-class correlation coefficient (ICC). The reproducibility includes the variability introduced in the image acquisition, like medical scans acquisition parameters and convolution kernels, that affects intensity-based features and tumor annotations made by physicians, that influences morphological descriptors of the lesion.For the reproducibility of radiomics features three studies were conducted on cases collected at Vall Hebron Oncology Institute (VHIO) on responders to oncology treatment. The studies focused on the variability due to the convolution kernel, image acquisition parameters, and the inter-observer lesion identification. The features selected were those features with a ICC higher than 0.7 in the three studies.The selected features based on reproducibility were evaluated for lesion malignancy classification using a different database. Results show better performance compared to several state-of-the-art methods including Principal Component Analysis (PCA), Kernel Discriminant Analysis via QR decomposition (KDAQR), LASSO, and an own built Convolutional Neural Network. |
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Berlin; Alemanya; July 2019 |
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IAM; 600.139; 600.145 |
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Admin @ si @ LTS2019 |
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3358 |
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Author |
Hanne Kause; Patricia Marquez; Andrea Fuster; Aura Hernandez-Sabate; Luc Florack; Debora Gil; Hans van Assen |
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Title |
Quality Assessment of Optical Flow in Tagging MRI |
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2015 |
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5th Dutch Bio-Medical Engineering Conference BME2015 |
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The Netherlands; January 2015 |
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BME |
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IAM; ADAS; 600.076; 600.075 |
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Admin @ si @ KMF2015 |
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2616 |
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