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Author Patricia Marquez; Debora Gil ; Aura Hernandez-Sabate edit   pdf
doi  isbn
openurl 
  Title Error Analysis for Lucas-Kanade Based Schemes Type Conference Article
  Year 2012 Publication 9th International Conference on Image Analysis and Recognition Abbreviated Journal  
  Volume 7324 Issue I Pages 184-191  
  Keywords Optical flow, Confidence measure, Lucas-Kanade, Cardiac Magnetic Resonance  
  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.  
  Address Aveiro, Portugal  
  Corporate Author Thesis  
  Publisher Springer-Verlag Berlin Heidelberg Place of Publication Editor  
  Language english Summary Language Original Title  
  Series Editor Campilho, Aurélio and Kamel, Mohamed Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-31294-6 Medium  
  Area Expedition Conference ICIAR  
  Notes IAM Approved no  
  Call Number (up) IAM @ iam @ MGH2012a Serial 1899  
Permanent link to this record
 

 
Author Ferran Poveda; Debora Gil ;Albert Andaluz ;Enric Marti edit   pdf
url  doi
openurl 
  Title Multiscale Tractography for Representing Heart Muscular Architecture Type Conference Article
  Year 2011 Publication In MICCAI 2011 Workshop on Computational Diffusion MRI Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Deep understanding of myocardial structure of the heart would unravel crucial knowledge for clinical and medical procedures. Although the muscular architecture of the heart has been debated by countless researchers, the controversy is still alive. Diffusion Tensor MRI, DT-MRI, is a unique imaging technique for computational validation of the muscular structure of the heart. By the complex arrangement of myocites, existing techniques can not provide comprehensive descriptions of the global muscular architecture. In this paper we introduce 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 indicate a global helical organization  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language english Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CDRMI  
  Notes IAM Approved no  
  Call Number (up) IAM @ iam @ PGA2011 Serial 1681  
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Author David Roche; Debora Gil; Jesus Giraldo edit   pdf
url  openurl
  Title Assessing agonist efficacy in an uncertain Em world Type Conference Article
  Year 2012 Publication 40th Keystone Symposia on mollecular and celular biology Abbreviated Journal  
  Volume Issue Pages 79  
  Keywords  
  Abstract 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.
 
  Address Fairmont Banff Springs, Banff, Alberta, Canada  
  Corporate Author Keystone Symposia Thesis  
  Publisher Keystone Symposia Place of Publication Editor A. Christopoulus and M. Bouvier  
  Language english Summary Language english Original Title  
  Series Editor Keystone Symposia Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference KSMCB  
  Notes IAM Approved no  
  Call Number (up) IAM @ iam @ RGG2012 Serial 1855  
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Author Carles Sanchez edit   pdf
openurl 
  Title Tracheal ring detection in bronchoscopy Type Report
  Year 2011 Publication CVC Technical Report Abbreviated Journal  
  Volume 168 Issue Pages  
  Keywords Bronchoscopy, tracheal ring, segmentation  
  Abstract Endoscopy is the process in which a camera is introduced inside a human.
Given that endoscopy provides realistic images (in contrast to other modalities) and allows non-invase minimal intervention procedures (which can aid in diagnosis and surgical interventions), its use has spreaded during last decades.
In this project we will focus on bronchoscopic procedures, during which the camera is introduced through the trachea in order to have a diagnostic of the patient. The diagnostic interventions are focused on: degree of stenosis (reduction in tracheal area), prosthesis or early diagnosis of tumors. In the first case, assessment of the luminal area and the calculation of the diameters of the tracheal rings are required. A main limitation is that all the process is done by hand,
which means that the doctor takes all the measurements and decisions just by looking at the screen. As far as we know there is no computational framework for helping the doctors in the diagnosis.
This project will consist of analysing bronchoscopic videos in order to extract useful information for the diagnostic of the degree of stenosis. In particular we will focus on segmentation of the tracheal rings. As a result of this project several strategies (for detecting tracheal rings) had been implemented in order to compare their performance.
 
  Address  
  Corporate Author Thesis Master's thesis  
  Publisher Place of Publication Editor Debora Gil, F.Javier Sanchez  
  Language english Summary Language english Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM;MV Approved no  
  Call Number (up) IAM @ iam @ San2011 Serial 1841  
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Author Sergio Vera; Debora Gil; Agnes Borras; F. Javier Sanchez; Frederic Perez; Marius G. Linguraru; Miguel Angel Gonzalez Ballester edit   pdf
doi  isbn
openurl 
  Title Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs Type Book Chapter
  Year 2012 Publication Workshop on Computational and Clinical Applications in Abdominal Imaging Abbreviated Journal  
  Volume 7029 Issue Pages 223–230  
  Keywords medial manifolds, abdomen.  
  Abstract Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing 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 avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our
method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs,
exploring the use of medial manifolds for the representation of multi-organ relations.
 
  Address Toronto; Canada;  
  Corporate Author Thesis  
  Publisher Springer Link Place of Publication Berlin Editor H. Yoshida et al  
  Language English Summary Language English Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-28556-1 Medium  
  Area Expedition Conference ABDI  
  Notes IAM;MV Approved no  
  Call Number (up) IAM @ iam @ VGB2012 Serial 1834  
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Author Sergio Vera; Debora Gil; Antonio Lopez; Miguel Angel Gonzalez Ballester edit   pdf
url  openurl
  Title Multilocal Creaseness Measure Type Journal
  Year 2012 Publication The Insight Journal Abbreviated Journal IJ  
  Volume Issue Pages  
  Keywords Ridges, Valley, Creaseness, Structure Tensor, Skeleton,  
  Abstract This document describes the implementation using the Insight Toolkit of an algorithm for detecting creases (ridges and valleys) in N-dimensional images, based on the Local Structure Tensor of the image. In addition to the filter used to calculate the creaseness image, a filter for the computation of the structure tensor is also included in this submission.  
  Address  
  Corporate Author Alma IT Systems Thesis  
  Publisher Place of Publication Editor  
  Language english Summary Language english Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM;ADAS; Approved no  
  Call Number (up) IAM @ iam @ VGL2012 Serial 1840  
Permanent link to this record
 

 
Author David Vazquez; Antonio Lopez; Daniel Ponsa; David Geronimo edit   pdf
doi  isbn
openurl 
  Title Interactive Training of Human Detectors Type Book Chapter
  Year 2013 Publication Multiodal Interaction in Image and Video Applications Abbreviated Journal  
  Volume 48 Issue Pages 169-182  
  Keywords Pedestrian Detection; Virtual World; AdaBoost; Domain Adaptation  
  Abstract Image based human detection remains as a challenging problem. Most promising detectors rely on classifiers trained with labelled samples. However, labelling is a manual labor intensive step. To overcome this problem we propose to collect images of pedestrians from a virtual city, i.e., with automatic labels, and train a pedestrian detector with them, which works fine when such virtual-world data are similar to testing one, i.e., real-world pedestrians in urban areas. When testing data is acquired in different conditions than training one, e.g., human detection in personal photo albums, dataset shift appears. In previous work, we cast this problem as one of domain adaptation and solve it with an active learning procedure. In this work, we focus on the same problem but evaluating a different set of faster to compute features, i.e., Haar, EOH and their combination. In particular, we train a classifier with virtual-world data, using such features and Real AdaBoost as learning machine. This classifier is applied to real-world training images. Then, a human oracle interactively corrects the wrong detections, i.e., few miss detections are manually annotated and some false ones are pointed out too. A low amount of manual annotation is fixed as restriction. Real- and virtual-world difficult samples are combined within what we call cool world and we retrain the classifier with this data. Our experiments show that this adapted classifier is equivalent to the one trained with only real-world data but requiring 90% less manual annotations.  
  Address Springer Heidelberg New York Dordrecht London  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1868-4394 ISBN 978-3-642-35931-6 Medium  
  Area Expedition Conference  
  Notes ADAS; 600.057; 600.054; 605.203 Approved no  
  Call Number (up) VLP2013; ADAS @ adas @ vlp2013 Serial 2193  
Permanent link to this record
 

 
Author Jiaolong Xu; David Vazquez; Sebastian Ramos; Antonio Lopez; Daniel Ponsa edit   pdf
doi  openurl
  Title Adapting a Pedestrian Detector by Boosting LDA Exemplar Classifiers Type Conference Article
  Year 2013 Publication CVPR Workshop on Ground Truth – What is a good dataset? Abbreviated Journal  
  Volume Issue Pages 688 - 693  
  Keywords Pedestrian Detection; Domain Adaptation  
  Abstract Training vision-based pedestrian detectors using synthetic datasets (virtual world) is a useful technique to collect automatically the training examples with their pixel-wise ground truth. However, as it is often the case, these detectors must operate in real-world images, experiencing a significant drop of their performance. In fact, this effect also occurs among different real-world datasets, i.e. detectors' accuracy drops when the training data (source domain) and the application scenario (target domain) have inherent differences. Therefore, in order to avoid this problem, it is required to adapt the detector trained with synthetic data to operate in the real-world scenario. In this paper, we propose a domain adaptation approach based on boosting LDA exemplar classifiers from both virtual and real worlds. We evaluate our proposal on multiple real-world pedestrian detection datasets. The results show that our method can efficiently adapt the exemplar classifiers from virtual to real world, avoiding drops in average precision over the 15%.  
  Address Portland; oregon; June 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CVPRW  
  Notes ADAS; 600.054; 600.057; 601.217 Approved yes  
  Call Number (up) XVR2013; ADAS @ adas @ xvr2013a Serial 2220  
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