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Author Aura Hernandez-Sabate; Debora Gil;Eduard Fernandez-Nofrerias;Petia Radeva; Enric Marti edit   pdf
doi  openurl
  Title (up) Approaching Artery Rigid Dynamics in IVUS Type Journal Article
  Year 2009 Publication IEEE Transactions on Medical Imaging Abbreviated Journal TMI  
  Volume 28 Issue 11 Pages 1670-1680  
  Keywords Fourier analysis; intravascular ultrasound (IVUS) dynamics; longitudinal motion; quality measures; tissue deformation.  
  Abstract Tissue biomechanical properties (like strain and stress) are playing an increasing role in diagnosis and long-term treatment of intravascular coronary diseases. Their assessment strongly relies on estimation of vessel wall deformation. Since intravascular ultrasound (IVUS) sequences allow visualizing vessel morphology and reflect its dynamics, this technique represents a useful tool for evaluation of tissue mechanical properties. Image misalignment introduced by vessel-catheter motion is a major artifact for a proper tracking of tissue deformation. In this work, we focus on compensating and assessing IVUS rigid in-plane motion due to heart beating. Motion parameters are computed by considering both the vessel geometry and its appearance in the image. Continuum mechanics laws serve to introduce a novel score measuring motion reduction in in vivo sequences. Synthetic experiments validate the proposed score as measure of motion parameters accuracy; whereas results in in vivo pullbacks show the reliability of the presented methodologies in clinical cases.  
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  ISSN 0278-0062 ISBN Medium  
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  Notes IAM; MILAB Approved no  
  Call Number IAM @ iam @ HGF2009 Serial 1545  
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Author Sonia Baeza; R.Domingo; M.Salcedo; G.Moragas; J.Deportos; I.Garcia Olive; Carles Sanchez; Debora Gil; Antoni Rosell edit  url
openurl 
  Title (up) Artificial Intelligence to Optimize Pulmonary Embolism Diagnosis During Covid-19 Pandemic by Perfusion SPECT/CT, a Pilot Study Type Journal Article
  Year 2021 Publication American Journal of Respiratory and Critical Care Medicine Abbreviated Journal  
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  Notes IAM; 600.145 Approved no  
  Call Number Admin @ si @ BDS2021 Serial 3591  
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Author Carles Sanchez; Oriol Ramos Terrades; Patricia Marquez; Enric Marti; J.Roncaries; Debora Gil edit  doi
openurl 
  Title (up) Automatic evaluation of practices in Moodle for Self Learning in Engineering Type Journal
  Year 2015 Publication Journal of Technology and Science Education Abbreviated Journal JOTSE  
  Volume 5 Issue 2 Pages 97-106  
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  Notes IAM; DAG; 600.075; 600.077 Approved no  
  Call Number Admin @ si @ SRM2015 Serial 2610  
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Author Ole Larsen; Petia Radeva; Enric Marti edit   pdf
doi  openurl
  Title (up) Bounds on the optimal elasticity parameters for a snake Type Journal Article
  Year 1995 Publication Image Analysis and Processing Abbreviated Journal  
  Volume Issue Pages 37-42  
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  Abstract This paper develops a formalism by which an estimate for the upper and lower bounds for the elasticity parameters for a snake can be obtained. Objects different in size and shape give rise to different bounds. The bounds can be obtained based on an analysis of the shape of the object of interest. Experiments on synthetic images show a good correlation between the estimated behaviour of the snake and the one actually observed. Experiments on real X-ray images show that the parameters for optimal segmentation lie within the estimated bounds.  
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  Notes MILAB;IAM Approved no  
  Call Number IAM @ iam @ LRM1995a Serial 1559  
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Author Juan Borrego-Carazo; Carles Sanchez; David Castells; Jordi Carrabina; Debora Gil edit   pdf
doi  openurl
  Title (up) BronchoPose: an analysis of data and model configuration for vision-based bronchoscopy pose estimation Type Journal Article
  Year 2023 Publication Computer Methods and Programs in Biomedicine Abbreviated Journal CMPB  
  Volume 228 Issue Pages 107241  
  Keywords Videobronchoscopy guiding; Deep learning; Architecture optimization; Datasets; Standardized evaluation framework; Pose estimation  
  Abstract Vision-based bronchoscopy (VB) models require the registration of the virtual lung model with the frames from the video bronchoscopy to provide effective guidance during the biopsy. The registration can be achieved by either tracking the position and orientation of the bronchoscopy camera or by calibrating its deviation from the pose (position and orientation) simulated in the virtual lung model. Recent advances in neural networks and temporal image processing have provided new opportunities for guided bronchoscopy. However, such progress has been hindered by the lack of comparative experimental conditions.
In the present paper, we share a novel synthetic dataset allowing for a fair comparison of methods. Moreover, this paper investigates several neural network architectures for the learning of temporal information at different levels of subject personalization. In order to improve orientation measurement, we also present a standardized comparison framework and a novel metric for camera orientation learning. Results on the dataset show that the proposed metric and architectures, as well as the standardized conditions, provide notable improvements to current state-of-the-art camera pose estimation in video bronchoscopy.
 
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  Publisher Elsevier Place of Publication Editor  
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  Notes IAM; Approved no  
  Call Number Admin @ si @ BSC2023 Serial 3702  
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