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Author C. Malagelada; Fosca De Iorio; Fernando Azpiroz; Anna Accarino; Santiago Segui; Petia Radeva; Juan R. Malagelada edit  openurl
  Title New Insight Into Intestinal Motor Function via Noninvasive Endoluminal Image Analysis Type Journal
  Year 2008 Publication Gastroenterology Abbreviated Journal  
  Volume 135 Issue 4 Pages 1155–1162  
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  Notes MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ MDA2008 Serial 1040  
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Author C. Butakoff; Simone Balocco; F.M. Sukno; C. Hoogendoorn; C. Tobon-Gomez; G. Avegliano; A.F. Frangi edit   pdf
doi  openurl
  Title Left-ventricular Epi- and Endocardium Extraction from 3D Ultrasound Images Using an Automatically Constructed 3D ASM Type Journal Article
  Year 2016 Publication Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization Abbreviated Journal CMBBE  
  Volume 4 Issue 5 Pages 265-280  
  Keywords ASM; cardiac segmentation; statistical model; shape model; 3D ultrasound; cardiac segmentation  
  Abstract In this paper, we propose an automatic method for constructing an active shape model (ASM) to segment the complete cardiac left ventricle in 3D ultrasound (3DUS) images, which avoids costly manual landmarking. The automatic construction of the ASM has already been addressed in the literature; however, the direct application of these methods to 3DUS is hampered by a high level of noise and artefacts. Therefore, we propose to construct the ASM by fusing the multidetector computed tomography data, to learn the shape, with the artificially generated 3DUS, in order to learn the neighbourhood of the boundaries. Our artificial images were generated by two approaches: a faster one that does not take into account the geometry of the transducer, and a more comprehensive one, implemented in Field II toolbox. The segmentation accuracy of our ASM was evaluated on 20 patients with left-ventricular asynchrony, demonstrating plausibility of the approach.  
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  ISSN 2168-1163 ISBN Medium  
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  Notes MILAB Approved no  
  Call Number Admin @ si @ BBS2016 Serial 2449  
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Author Santiago Segui; Michal Drozdzal; Ekaterina Zaytseva; Fernando Azpiroz; Petia Radeva; Jordi Vitria edit   pdf
doi  openurl
  Title Detection of wrinkle frames in endoluminal videos using betweenness centrality measures for images Type Journal Article
  Year 2014 Publication IEEE Transactions on Information Technology in Biomedicine Abbreviated Journal TITB  
  Volume 18 Issue 6 Pages 1831-1838  
  Keywords Wireless Capsule Endoscopy; Small Bowel Motility Dysfunction; Contraction Detection; Structured Prediction; Betweenness Centrality  
  Abstract Intestinal contractions are one of the most important events to diagnose motility pathologies of the small intestine. When visualized by wireless capsule endoscopy (WCE), the sequence of frames that represents a contraction is characterized by a clear wrinkle structure in the central frames that corresponds to the folding of the intestinal wall. In this paper we present a new method to robustly detect wrinkle frames in full WCE videos by using a new mid-level image descriptor that is based on a centrality measure proposed for graphs. We present an extended validation, carried out in a very large database, that shows that the proposed method achieves state of the art performance for this task.  
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  Notes OR; MILAB; 600.046;MV Approved no  
  Call Number Admin @ si @ SDZ2014 Serial 2385  
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Author Xavier Baro; Sergio Escalera; Jordi Vitria; Oriol Pujol; Petia Radeva edit  doi
openurl 
  Title Traffic Sign Recognition Using Evolutionary Adaboost Detection and Forest-ECOC Classification Type Journal Article
  Year 2009 Publication IEEE Transactions on Intelligent Transportation Systems Abbreviated Journal TITS  
  Volume 10 Issue 1 Pages 113–126  
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  Abstract The high variability of sign appearance in uncontrolled environments has made the detection and classification of road signs a challenging problem in computer vision. In this paper, we introduce a novel approach for the detection and classification of traffic signs. Detection is based on a boosted detectors cascade, trained with a novel evolutionary version of Adaboost, which allows the use of large feature spaces. Classification is defined as a multiclass categorization problem. A battery of classifiers is trained to split classes in an Error-Correcting Output Code (ECOC) framework. We propose an ECOC design through a forest of optimal tree structures that are embedded in the ECOC matrix. The novel system offers high performance and better accuracy than the state-of-the-art strategies and is potentially better in terms of noise, affine deformation, partial occlusions, and reduced illumination.  
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  ISSN 1524-9050 ISBN Medium  
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  Notes OR;MILAB;HuPBA;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ BEV2008 Serial 1116  
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Author Sergio Escalera; Oriol Pujol; Petia Radeva edit  doi
openurl 
  Title Separability of Ternary Codes for Sparse Designs of Error-Correcting Output Codes Type Journal Article
  Year 2009 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 30 Issue 3 Pages 285–297  
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  Abstract Error Correcting Output Codes (ECOC) represent a successful framework to deal with multi-class categorization problems based on combining binary classifiers. In this paper, we present a new formulation of the ternary ECOC distance and the error-correcting capabilities in the ternary ECOC framework. Based on the new measure, we stress on how to design coding matrices preventing codification ambiguity and propose a new Sparse Random coding matrix with ternary distance maximization. The results on the UCI Repository and in a real speed traffic categorization problem show that when the coding design satisfies the new ternary measures, significant performance improvement is obtained independently of the decoding strategy applied.  
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  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2009a Serial 1153  
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