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Antonio Hernandez; Carlo Gatta; Sergio Escalera; Laura Igual; Victoria Martin-Yuste; Manel Sabate; Petia Radeva |
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Title |
Accurate coronary centerline extraction, caliber estimation and catheter detection in angiographies |
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2012 |
Publication ![sorted by Publication field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
IEEE Transactions on Information Technology in Biomedicine |
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TITB |
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16 |
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6 |
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1332-1340 |
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Segmentation of coronary arteries in X-Ray angiography is a fundamental tool to evaluate arterial diseases and choose proper coronary treatment. The accurate segmentation of coronary arteries has become an important topic for the registration of different modalities which allows physicians rapid access to different medical imaging information from Computed Tomography (CT) scans or Magnetic Resonance Imaging (MRI). In this paper, we propose an accurate fully automatic algorithm based on Graph-cuts for vessel centerline extraction, caliber estimation, and catheter detection. Vesselness, geodesic paths, and a new multi-scale edgeness map are combined to customize the Graph-cuts approach to the segmentation of tubular structures, by means of a global optimization of the Graph-cuts energy function. Moreover, a novel supervised learning methodology that integrates local and contextual information is proposed for automatic catheter detection. We evaluate the method performance on three datasets coming from different imaging systems. The method performs as good as the expert observer w.r.t. centerline detection and caliber estimation. Moreover, the method discriminates between arteries and catheter with an accuracy of 96.5%, sensitivity of 72%, and precision of 97.4%. |
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1089-7771 |
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MILAB;HuPBA |
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Admin @ si @ HGE2012 |
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2141 |
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Xavier Baro; Sergio Escalera; Jordi Vitria; Oriol Pujol; Petia Radeva |
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Title |
Traffic Sign Recognition Using Evolutionary Adaboost Detection and Forest-ECOC Classification |
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2009 |
Publication ![sorted by Publication field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
IEEE Transactions on Intelligent Transportation Systems |
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TITS |
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10 |
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1 |
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113–126 |
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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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1524-9050 |
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OR;MILAB;HuPBA;MV |
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BCNPCL @ bcnpcl @ BEV2008 |
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1116 |
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Maria Salamo; Sergio Escalera |
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Increasing Retrieval Quality in Conversational Recommenders |
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2011 |
Publication ![sorted by Publication field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
IEEE Transactions on Knowledge and Data Engineering |
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TKDE |
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99 |
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1-1 |
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IF JCR CCIA 2.286 2009 24/103
JCR Impact Factor 2010: 1.851
A major task of research in conversational recommender systems is personalization. Critiquing is a common and powerful form of feedback, where a user can express her feature preferences by applying a series of directional critiques over the recommendations instead of providing specific preference values. Incremental Critiquing is a conversational recommender system that uses critiquing as a feedback to efficiently personalize products. The expectation is that in each cycle the system retrieves the products that best satisfy the user’s soft product preferences from a minimal information input. In this paper, we present a novel technique that increases retrieval quality based on a combination of compatibility and similarity scores. Under the hypothesis that a user learns Turing the recommendation process, we propose two novel exponential reinforcement learning approaches for compatibility that take into account both the instant at which the user makes a critique and the number of satisfied critiques. Moreover, we consider that the impact of features on the similarity differs according to the preferences manifested by the user. We propose a global weighting approach that uses a common weight for nearest cases in order to focus on groups of relevant products. We show that our methodology significantly improves recommendation efficiency in four data sets of different sizes in terms of session length in comparison with state-of-the-art approaches. Moreover, our recommender shows higher robustness against noisy user data when compared to classical approaches |
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IEEE |
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1041-4347 |
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MILAB; HuPBA |
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Admin @ si @ SaE2011 |
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1713 |
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Amir A.Amini; Yasheng Chen; Mohamed Elayyadi; Petia Radeva |
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Tag Surface Reconstruction and Tracking of Myocardial Beads from SPAMM-MRI with Parametric B-Spline Surfaces |
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2001 |
Publication ![sorted by Publication field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
IEEE Transactions on Medical Imaging |
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TMI |
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20 |
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2 |
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94–103 |
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B-spline surfaces, cardiac motion, myocardial beads, myocardial infarction, tagged MRI. |
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Magnetic resonance imaging (MRI) is unique in its ability to noninvasively and selectively alter tissue magnetization, and create tag planes intersecting image slices. The resulting grid of signal voids allows for tracking deformations of tissues in otherwise homogeneous-signal myocardial regions. In this paper, we propose a specific spatial modulation of magnetization (SPAMM) imaging protocol together with efficient techniques for measurement of three-dimensional (3-D) motion of material points of the human heart (referred to as myocardial beads) from images collected with the SPAMM method. The techniques make use of tagged images in orthogonal views by explicitly reconstructing 3-D B-spline surface representation of tag planes (tag planes in two orthogonal orientations intersecting the short-axis (SA) image slices and tag planes in an orientation orthogonal to the short-axis tag planes intersecting long-axis (LA) image slices). The developed methods allow for viewing deformations of 3-D tag surfaces, spatial correspondence of long-axis and short-axis image slice and tag positions, as well as nonrigid movement of myocardial beads as a function of time. |
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BCNPCL @ bcnpcl @ ACE2001; IAM @ iam @ ACE2001 |
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180 |
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Fernando Vilariño; Panagiota Spyridonos; Fosca De Iorio; Jordi Vitria; Fernando Azpiroz; Petia Radeva |
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Title |
Intestinal Motility Assessment With Video Capsule Endoscopy: Automatic Annotation of Phasic Intestinal Contractions |
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Journal Article |
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2010 |
Publication ![sorted by Publication field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
IEEE Transactions on Medical Imaging |
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TMI |
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29 |
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2 |
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246-259 |
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Intestinal motility assessment with video capsule endoscopy arises as a novel and challenging clinical fieldwork. This technique is based on the analysis of the patterns of intestinal contractions shown in a video provided by an ingestible capsule with a wireless micro-camera. The manual labeling of all the motility events requires large amount of time for offline screening in search of findings with low prevalence, which turns this procedure currently unpractical. In this paper, we propose a machine learning system to automatically detect the phasic intestinal contractions in video capsule endoscopy, driving a useful but not feasible clinical routine into a feasible clinical procedure. Our proposal is based on a sequential design which involves the analysis of textural, color, and blob features together with SVM classifiers. Our approach tackles the reduction of the imbalance rate of data and allows the inclusion of domain knowledge as new stages in the cascade. We present a detailed analysis, both in a quantitative and a qualitative way, by providing several measures of performance and the assessment study of interobserver variability. Our system performs at 70% of sensitivity for individual detection, whilst obtaining equivalent patterns to those of the experts for density of contractions. |
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IEEE |
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0278-0062 |
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800 |
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MILAB;MV;OR;SIAI |
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BCNPCL @ bcnpcl @ VSD2010; IAM @ iam @ VSI2010 |
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1281 |
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