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Author Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva edit   pdf
doi  openurl
  Title Adaptable image cuts for motility inspection using WCE Type Journal Article
  Year 2013 Publication Computerized Medical Imaging and Graphics Abbreviated Journal CMIG  
  Volume 37 Issue 1 Pages (up) 72-80  
  Keywords  
  Abstract The Wireless Capsule Endoscopy (WCE) technology allows the visualization of the whole small intestine tract. Since the capsule is freely moving, mainly by the means of peristalsis, the data acquired during the study gives a lot of information about the intestinal motility. However, due to: (1) huge amount of frames, (2) complex intestinal scene appearance and (3) intestinal dynamics that make difficult the visualization of the small intestine physiological phenomena, the analysis of the WCE data requires computer-aided systems to speed up the analysis. In this paper, we propose an efficient algorithm for building a novel representation of the WCE video data, optimal for motility analysis and inspection. The algorithm transforms the 3D video data into 2D longitudinal view by choosing the most informative, from the intestinal motility point of view, part of each frame. This step maximizes the lumen visibility in its longitudinal extension. The task of finding “the best longitudinal view” has been defined as a cost function optimization problem which global minimum is obtained by using Dynamic Programming. Validation on both synthetic data and WCE data shows that the adaptive longitudinal view is a good alternative to the traditional motility analysis done by video analysis. The proposed novel data representation a new, holistic insight into the small intestine motility, allowing to easily define and analyze motility events that are difficult to spot by analyzing WCE video. Moreover, the visual inspection of small intestine motility is 4 times faster then by means of video skimming of the WCE.  
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  Notes MILAB; OR; 600.046; 605.203 Approved no  
  Call Number Admin @ si @ DSM2012 Serial 2151  
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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  
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Author Marc Bolaños; Mariella Dimiccoli; Petia Radeva edit   pdf
doi  openurl
  Title Towards Storytelling from Visual Lifelogging: An Overview Type Journal Article
  Year 2017 Publication IEEE Transactions on Human-Machine Systems Abbreviated Journal THMS  
  Volume 47 Issue 1 Pages (up) 77 - 90  
  Keywords  
  Abstract Visual lifelogging consists of acquiring images that capture the daily experiences of the user by wearing a camera over a long period of time. The pictures taken offer considerable potential for knowledge mining concerning how people live their lives, hence, they open up new opportunities for many potential applications in fields including healthcare, security, leisure and
the quantified self. However, automatically building a story from a huge collection of unstructured egocentric data presents major challenges. This paper provides a thorough review of advances made so far in egocentric data analysis, and in view of the current state of the art, indicates new lines of research to move us towards storytelling from visual lifelogging.
 
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  Notes MILAB; 601.235 Approved no  
  Call Number Admin @ si @ BDR2017 Serial 2712  
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Author Alvaro Cepero; Albert Clapes; Sergio Escalera edit   pdf
doi  openurl
  Title Automatic non-verbal communication skills analysis: a quantitative evaluation Type Journal Article
  Year 2015 Publication AI Communications Abbreviated Journal AIC  
  Volume 28 Issue 1 Pages (up) 87-101  
  Keywords Social signal processing; human behavior analysis; multi-modal data description; multi-modal data fusion; non-verbal communication analysis; e-Learning  
  Abstract The oral communication competence is defined on the top of the most relevant skills for one's professional and personal life. Because of the importance of communication in our activities of daily living, it is crucial to study methods to evaluate and provide the necessary feedback that can be used in order to improve these communication capabilities and, therefore, learn how to express ourselves better. In this work, we propose a system capable of evaluating quantitatively the quality of oral presentations in an automatic fashion. The system is based on a multi-modal RGB, depth, and audio data description and a fusion approach in order to recognize behavioral cues and train classifiers able to eventually predict communication quality levels. The performance of the proposed system is tested on a novel dataset containing Bachelor thesis' real defenses, presentations from an 8th semester Bachelor courses, and Master courses' presentations at Universitat de Barcelona. Using as groundtruth the marks assigned by actual instructors, our system achieves high performance categorizing and ranking presentations by their quality, and also making real-valued mark predictions.  
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  ISSN 0921-7126 ISBN Medium  
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  Notes HUPBA;MILAB Approved no  
  Call Number Admin @ si @ CCE2015 Serial 2549  
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Author Misael Rosales; Petia Radeva; Oriol Rodriguez-Leor; Debora Gil edit   pdf
doi  openurl
  Title Modelling of image-catheter motion for 3-D IVUS Type Journal Article
  Year 2009 Publication Medical image analysis Abbreviated Journal MIA  
  Volume 13 Issue 1 Pages (up) 91-104  
  Keywords Intravascular ultrasound (IVUS); Motion estimation; Motion decomposition; Fourier  
  Abstract 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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  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ RRR2009 Serial 1646  
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