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Author |
Aura Hernandez-Sabate; Debora Gil; Petia Radeva; E.N.Nofrerias |
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Title |
Anisotropic processing of image structures for adventitia detection in intravascular ultrasound images |
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Conference Article |
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Year |
2004 |
Publication |
Proc. Computers in Cardiology |
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31 |
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Pages |
229-232 |
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Abstract  |
The adventitia layer appears as a weak edge in IVUS images with a non-uniform grey level, which difficulties its detection. In order to enhance edges, we apply an anisotropic filter that homogenizes the grey level along the image significant structures (ridges, valleys and edges). A standard edge detector applied to the filtered image yields a set of candidate points prone to be unconnected. The final model is obtained by interpolating the former line segments along the tangent direction to the level curves of the filtered image with an anisotropic contour closing technique based on functional extension principles |
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Chicago (USA) |
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IAM; MILAB |
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no |
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IAM @ iam @ HGR2004 |
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1555 |
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Author |
David Roche; Debora Gil; Jesus Giraldo |
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Title |
Assessing agonist efficacy in an uncertain Em world |
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Conference Article |
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Year |
2012 |
Publication |
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 |
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IAM @ iam @ RGG2012 |
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1855 |
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Author |
Jose Elias Yauri; Aura Hernandez-Sabate; Pau Folch; Debora Gil |
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Title |
Mental Workload Detection Based on EEG Analysis |
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Conference Article |
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Year |
2021 |
Publication |
Artificial Intelligent Research and Development. Proceedings 23rd International Conference of the Catalan Association for Artificial Intelligence. |
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339 |
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268-277 |
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Cognitive states; Mental workload; EEG analysis; Neural Networks. |
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The study of mental workload becomes essential for human work efficiency, health conditions and to avoid accidents, since workload compromises both performance and awareness. Although workload has been widely studied using several physiological measures, minimising the sensor network as much as possible remains both a challenge and a requirement.
Electroencephalogram (EEG) signals have shown a high correlation to specific cognitive and mental states like workload. However, there is not enough evidence in the literature to validate how well models generalize in case of new subjects performing tasks of a workload similar to the ones included during model’s training.
In this paper we propose a binary neural network to classify EEG features across different mental workloads. Two workloads, low and medium, are induced using two variants of the N-Back Test. The proposed model was validated in a dataset collected from 16 subjects and shown a high level of generalization capability: model reported an average recall of 81.81% in a leave-one-out subject evaluation. |
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Virtual; October 20-22 2021 |
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CCIA |
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IAM; 600.139; 600.118; 600.145 |
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Call Number |
Admin @ si @ |
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3723 |
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Author |
Esmitt Ramirez; Carles Sanchez; Debora Gil |
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Title |
Localizing Pulmonary Lesions Using Fuzzy Deep Learning |
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Conference Article |
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Year |
2019 |
Publication |
21st International Symposium on Symbolic and Numeric Algorithms for Scientific Computing |
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290-294 |
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The usage of medical images is part of the clinical daily in several healthcare centers around the world. Particularly, Computer Tomography (CT) images are an important key in the early detection of suspicious lung lesions. The CT image exploration allows the detection of lung lesions before any invasive procedure (e.g. bronchoscopy, biopsy). The effective localization of lesions is performed using different image processing and computer vision techniques. Lately, the usage of deep learning models into medical imaging from detection to prediction shown that is a powerful tool for Computer-aided software. In this paper, we present an approach to localize pulmonary lung lesion using fuzzy deep learning. Our approach uses a simple convolutional neural network based using the LIDC-IDRI dataset. Each image is divided into patches associated a probability vector (fuzzy) according their belonging to anatomical structures on a CT. We showcase our approach as part of a full CAD system to exploration, planning, guiding and detection of pulmonary lesions. |
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Timisoara; Rumania; September 2019 |
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SYNASC |
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IAM; 600.145; 600.140; 601.337; 601.323 |
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no |
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Call Number |
Admin @ si @ RSG2019 |
Serial |
3531 |
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Author |
Debora Gil; Jaume Garcia; Ruth Aris; Guillaume Houzeaux; Manuel Vazquez |
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Title |
A Riemmanian approach to cardiac fiber architecture modelling |
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Conference Article |
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Year |
2009 |
Publication |
1st International Conference on Mathematical & Computational Biomedical Engineering |
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59-62 |
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Keywords |
cardiac fiber architecture; diffusion tensor magnetic resonance imaging; differential (Rie- mannian) geometry. |
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There is general consensus that myocardial fiber architecture should be modelled in order to fully understand the electromechanical properties of the Left Ventricle (LV). Diffusion Tensor magnetic resonance Imaging (DTI) is the reference image modality for rapid measurement of fiber orientations by means of the tensor principal eigenvectors. In this work, we present a mathematical framework for across subject comparison of the local geometry of the LV anatomy including the fiber architecture from the statistical analysis of DTI studies. We use concepts of differential geometry for defining a parametric domain suitable for statistical analysis of a low number of samples. We use Riemannian metrics to define a consistent computation of DTI principal eigenvector modes of variation. Our framework has been applied to build an atlas of the LV fiber architecture from 7 DTI normal canine hearts. |
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Swansea (UK) |
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Nithiarasu, R.L.R.V.L. |
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CMBE |
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IAM |
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IAM @ iam @ FGA2009 |
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1520 |
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Author |
Francesco Brughi; Debora Gil; Llorenç Badiella; Eva Jove Casabella; Oriol Ramos Terrades |
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Title |
Exploring the impact of inter-query variability on the performance of retrieval systems |
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Conference Article |
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Year |
2014 |
Publication |
11th International Conference on Image Analysis and Recognition |
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8814 |
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413–420 |
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This paper introduces a framework for evaluating the performance of information retrieval systems. Current evaluation metrics provide an average score that does not consider performance variability across the query set. In this manner, conclusions lack of any statistical significance, yielding poor inference to cases outside the query set and possibly unfair comparisons. We propose to apply statistical methods in order to obtain a more informative measure for problems in which different query classes can be identified. In this context, we assess the performance variability on two levels: overall variability across the whole query set and specific query class-related variability. To this end, we estimate confidence bands for precision-recall curves, and we apply ANOVA in order to assess the significance of the performance across different query classes. |
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Algarve; Portugal; October 2014 |
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Springer International Publishing |
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LNCS |
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0302-9743 |
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978-3-319-11757-7 |
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ICIAR |
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IAM; DAG; 600.060; 600.061; 600.077; 600.075 |
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no |
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Admin @ si @ BGB2014 |
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2559 |
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Author |
Guillermo Torres; Jan Rodríguez Dueñas; Sonia Baeza; Antoni Rosell; Carles Sanchez; Debora Gil |
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Title |
Prediction of Malignancy in Lung Cancer using several strategies for the fusion of Multi-Channel Pyradiomics Images |
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Conference Article |
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2023 |
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7th Workshop on Digital Image Processing for Medical and Automotive Industry in the framework of SYNASC 2023 |
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This study shows the generation process and the subsequent study of the representation space obtained by extracting GLCM texture features from computer-aided tomography (CT) scans of pulmonary nodules (PN). For this, data from 92 patients from the Germans Trias i Pujol University Hospital were used. The workflow focuses on feature extraction using Pyradiomics and the VGG16 Convolutional Neural Network (CNN). The aim of the study is to assess whether the data obtained have a positive impact on the diagnosis of lung cancer (LC). To design a machine learning (ML) model training method that allows generalization, we train SVM and neural network (NN) models, evaluating diagnosis performance using metrics defined at slice and nodule level. |
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DIPMAI |
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IAM |
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Admin @ si @ TRB2023 |
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3926 |
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Author |
Aura Hernandez-Sabate; Petia Radeva; Antonio Tovar; Debora Gil |
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Title |
Vessel structures alignment by spectral analysis of ivus sequences |
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Conference Article |
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2006 |
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Proc. of CVII, MICCAI Workshop |
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39-36 |
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Three-dimensional intravascular ultrasound (IVUS) allows to visualize and obtain volumetric measurements of coronary lesions through an exploration of the cross sections and longitudinal views of arteries. However, the visualization and subsequent morpho-geometric measurements in IVUS longitudinal cuts are subject to distortion caused by periodic image/vessel motion around the IVUS catheter. Usually, to overcome the image motion artifact ECG-gating and image-gated approaches are proposed, leading to slowing the pullback acquisition or disregarding part of IVUS data. In this paper, we argue that the image motion is due to 3-D vessel geometry as well as cardiac dynamics, and propose a dynamic model based on the tracking of an elliptical vessel approximation to recover the rigid transformation and align IVUS images without loosing any IVUS data. We report an extensive validation with synthetic simulated data and in vivo IVUS sequences of 30 patients achieving an average reduction of the image artifact of 97% in synthetic data and 79% in real-data. Our study shows that IVUS alignment improves longitudinal analysis of the IVUS data and is a necessary step towards accurate reconstruction and volumetric measurements of 3-D IVUS. |
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Copenhaguen (Denmark), |
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1st International Wokshop on Computer Vision for Intravascular and Intracardiac Imaging (CVII’06) |
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IAM; MILAB |
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IAM @ iam @ HRT2006 |
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1552 |
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Author |
Carles Sanchez; Debora Gil; Antoni Rosell; Albert Andaluz; F. Javier Sanchez |
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Title |
Segmentation of Tracheal Rings in Videobronchoscopy combining Geometry and Appearance |
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Conference Article |
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2013 |
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Proceedings of the International Conference on Computer Vision Theory and Applications |
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1 |
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153--161 |
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Video-bronchoscopy, tracheal ring segmentation, trachea geometric and appearance model |
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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 |
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Barcelona; February 2013 |
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SciTePress |
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Portugal |
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Sebastiano Battiato and José Braz |
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LNCS |
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978-989-8565-47-1 |
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800 |
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VISAPP |
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IAM;MV; 600.044; 600.047; 600.060; 605.203 |
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IAM @ iam @ SGR2013 |
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2123 |
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Cristina Cañero; Petia Radeva; Oriol Pujol; Ricardo Toledo; Debora Gil; J. Saludes; Juan J. Villanueva; B. Garcia del Blanco; J. Mauri; E. Fernandez-Nofrerias; J.A. Gomez-Hospital; E. Iraculis; J. Comin; C. Quiles; F. Jara; A. Cequier; E. Esplugas |
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Optimal Stent Implantation: Three-dimensional Evaluation of the Mutual Position of Stent and Vessel via Intracoronary Ecography |
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1999 |
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Proceedings of International Conference on Computer in Cardiology (CIC´99) |
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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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MILAB; RV; IAM; ADAS; HuPBA |
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IAM @ iam @ CRP1999a |
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1491 |
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