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Author David Rotger; Misael Rosales; Jaume Garcia; Oriol Pujol ; Josefina Mauri; Petia Radeva edit   pdf
openurl 
  Title Active Vessel: A New Multimedia Workstation for Intravascular Ultrasound and Angiography Fusion Type Journal Article
  Year 2003 Publication Computers in Cardiology Abbreviated Journal  
  Volume 30 Issue Pages (up) 65-68  
  Keywords  
  Abstract AcriveVessel is a new multimedia workstation which enables the visualization, acquisition and handling of both image modalities, on- and ofline. It enables DICOM v3.0 decompression and browsing, video acquisition,repmduction and storage for IntraVascular UltraSound (IVUS) and angiograms with their corresponding ECG,automatic catheter segmentation in angiography images (using fast marching algorithm). BSpline models definition for vessel layers on IVUS images sequence and an extensively validated tool to fuse information. This approach defines the correspondence of every IVUS image with its correspondent point in the angiogram and viceversa. The 3 0 reconstruction of the NUS catheterhessel enables real distance measurements as well as threedimensional visualization showing vessel tortuosity in the space.  
  Address  
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  Area Expedition Conference  
  Notes IAM;MILAB;HuPBA Approved no  
  Call Number IAM @ iam @ RRG2003 Serial 1647  
Permanent link to this record
 

 
Author Gerard Canal; Sergio Escalera; Cecilio Angulo edit   pdf
doi  openurl
  Title A Real-time Human-Robot Interaction system based on gestures for assistive scenarios Type Journal Article
  Year 2016 Publication Computer Vision and Image Understanding Abbreviated Journal CVIU  
  Volume 149 Issue Pages (up) 65-77  
  Keywords Gesture recognition; Human Robot Interaction; Dynamic Time Warping; Pointing location estimation  
  Abstract Natural and intuitive human interaction with robotic systems is a key point to develop robots assisting people in an easy and effective way. In this paper, a Human Robot Interaction (HRI) system able to recognize gestures usually employed in human non-verbal communication is introduced, and an in-depth study of its usability is performed. The system deals with dynamic gestures such as waving or nodding which are recognized using a Dynamic Time Warping approach based on gesture specific features computed from depth maps. A static gesture consisting in pointing at an object is also recognized. The pointed location is then estimated in order to detect candidate objects the user may refer to. When the pointed object is unclear for the robot, a disambiguation procedure by means of either a verbal or gestural dialogue is performed. This skill would lead to the robot picking an object in behalf of the user, which could present difficulties to do it by itself. The overall system — which is composed by a NAO and Wifibot robots, a KinectTM v2 sensor and two laptops — is firstly evaluated in a structured lab setup. Then, a broad set of user tests has been completed, which allows to assess correct performance in terms of recognition rates, easiness of use and response times.  
  Address  
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  Publisher Elsevier B.V. Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes HuPBA;MILAB; Approved no  
  Call Number Admin @ si @ CEA2016 Serial 2768  
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Author Simone Balocco; Carlo Gatta; Francesco Ciompi; A. Wahle; Petia Radeva; S. Carlier; G. Unal; E. Sanidas; F. Mauri; X. Carillo; T. Kovarnik; C. Wang; H. Chen; T. P. Exarchos; D. I. Fotiadis; F. Destrempes; G. Cloutier; Oriol Pujol; Marina Alberti; E. G. Mendizabal-Ruiz; M. Rivera; T. Aksoy; R. W. Downe; I. A. Kakadiaris edit   pdf
doi  openurl
  Title Standardized evaluation methodology and reference database for evaluating IVUS image segmentation Type Journal Article
  Year 2014 Publication Computerized Medical Imaging and Graphics Abbreviated Journal CMIG  
  Volume 38 Issue 2 Pages (up) 70-90  
  Keywords IVUS (intravascular ultrasound); Evaluation framework; Algorithm comparison; Image segmentation  
  Abstract This paper describes an evaluation framework that allows a standardized and quantitative comparison of IVUS lumen and media segmentation algorithms. This framework has been introduced at the MICCAI 2011 Computing and Visualization for (Intra)Vascular Imaging (CVII) workshop, comparing the results of eight teams that participated.
We describe the available data-base comprising of multi-center, multi-vendor and multi-frequency IVUS datasets, their acquisition, the creation of the reference standard and the evaluation measures. The approaches address segmentation of the lumen, the media, or both borders; semi- or fully-automatic operation; and 2-D vs. 3-D methodology. Three performance measures for quantitative analysis have
been proposed. The results of the evaluation indicate that segmentation of the vessel lumen and media is possible with an accuracy that is comparable to manual annotation when semi-automatic methods are used, as well as encouraging results can be obtained also in case of fully-automatic segmentation. The analysis performed in this paper also highlights the challenges in IVUS segmentation that remains to be
solved.
 
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB; LAMP; HuPBA; 600.046; 600.063; 600.079 Approved no  
  Call Number Admin @ si @ BGC2013 Serial 2314  
Permanent link to this record
 

 
Author Frederic Sampedro; Anna Domenech; Sergio Escalera; Ignasi Carrio edit  doi
openurl 
  Title Computing quantitative indicators of structural renal damage in pediatric DMSA scans Type Journal Article
  Year 2017 Publication Revista Española de Medicina Nuclear e Imagen Molecular Abbreviated Journal REMNIM  
  Volume 36 Issue 2 Pages (up) 72-77  
  Keywords  
  Abstract OBJECTIVES:
The proposal and implementation of a computational framework for the quantification of structural renal damage from 99mTc-dimercaptosuccinic acid (DMSA) scans. The aim of this work is to propose, implement, and validate a computational framework for the quantification of structural renal damage from DMSA scans and in an observer-independent manner.
MATERIALS AND METHODS:
From a set of 16 pediatric DMSA-positive scans and 16 matched controls and using both expert-guided and automatic approaches, a set of image-derived quantitative indicators was computed based on the relative size, intensity and histogram distribution of the lesion. A correlation analysis was conducted in order to investigate the association of these indicators with other clinical data of interest in this scenario, including C-reactive protein (CRP), white cell count, vesicoureteral reflux, fever, relative perfusion, and the presence of renal sequelae in a 6-month follow-up DMSA scan.
RESULTS:
A fully automatic lesion detection and segmentation system was able to successfully classify DMSA-positive from negative scans (AUC=0.92, sensitivity=81% and specificity=94%). The image-computed relative size of the lesion correlated with the presence of fever and CRP levels (p<0.05), and a measurement derived from the distribution histogram of the lesion obtained significant performance results in the detection of permanent renal damage (AUC=0.86, sensitivity=100% and specificity=75%).
CONCLUSIONS:
The proposal and implementation of a computational framework for the quantification of structural renal damage from DMSA scans showed a promising potential to complement visual diagnosis and non-imaging indicators.
 
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  Notes HuPBA;MILAB; no menciona Approved no  
  Call Number Admin @ si @ SDE2017 Serial 2842  
Permanent link to this record
 

 
Author Julio C. S. Jacques Junior; Yagmur Gucluturk; Marc Perez; Umut Guçlu; Carlos Andujar; Xavier Baro; Hugo Jair Escalante; Isabelle Guyon; Marcel A. J. van Gerven; Rob van Lier; Sergio Escalera edit  doi
openurl 
  Title First Impressions: A Survey on Vision-Based Apparent Personality Trait Analysis Type Journal Article
  Year 2022 Publication IEEE Transactions on Affective Computing Abbreviated Journal TAC  
  Volume 13 Issue 1 Pages (up) 75-95  
  Keywords Personality computing; first impressions; person perception; big-five; subjective bias; computer vision; machine learning; nonverbal signals; facial expression; gesture; speech analysis; multi-modal recognition  
  Abstract Personality analysis has been widely studied in psychology, neuropsychology, and signal processing fields, among others. From the past few years, it also became an attractive research area in visual computing. From the computational point of view, by far speech and text have been the most considered cues of information for analyzing personality. However, recently there has been an increasing interest from the computer vision community in analyzing personality from visual data. Recent computer vision approaches are able to accurately analyze human faces, body postures and behaviors, and use these information to infer apparent personality traits. Because of the overwhelming research interest in this topic, and of the potential impact that this sort of methods could have in society, we present in this paper an up-to-date review of existing vision-based approaches for apparent personality trait recognition. We describe seminal and cutting edge works on the subject, discussing and comparing their distinctive features and limitations. Future venues of research in the field are identified and discussed. Furthermore, aspects on the subjectivity in data labeling/evaluation, as well as current datasets and challenges organized to push the research on the field are reviewed.  
  Address 1 Jan.-March 2022  
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  Notes HuPBA Approved no  
  Call Number Admin @ si @ JGP2022 Serial 3724  
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