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Author Rui Hua; Oriol Pujol; Francesco Ciompi; Marina Alberti; Simone Balocco; J. Mauri; Petia Radeva edit   pdf
openurl 
  Title (down) Stent Strut Detection by Classifying a Wide Set of IVUS Features Type Conference Article
  Year 2012 Publication Computed Assisted Stenting Workshop Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Nice, France  
  Corporate Author Thesis  
  Publisher 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 STENT  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ HPC2012 Serial 2169  
Permanent link to this record
 

 
Author Francesco Ciompi; Simone Balocco; Carles Caus; J. Mauri; Petia Radeva edit  doi
isbn  openurl
  Title (down) Stent shape estimation through a comprehensive interpretation of intravascular ultrasound images Type Conference Article
  Year 2013 Publication 16th International Conference on Medical Image Computing and Computer Assisted Intervention Abbreviated Journal  
  Volume 8150 Issue 2 Pages 345-352  
  Keywords  
  Abstract We present a method for automatic struts detection and stent shape estimation in cross-sectional intravascular ultrasound images. A stent shape is first estimated through a comprehensive interpretation of the vessel morphology, performed using a supervised context-aware multi-class classification scheme. Then, the successive strut identification exploits both local appearance and the defined stent shape. The method is tested on 589 images obtained from 80 patients, achieving a F-measure of 74.1% and an averaged distance between manual and automatic struts of 0.10 mm.  
  Address Nagoya; Japan; September 2013  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-40762-8 Medium  
  Area Expedition Conference MICCAI  
  Notes MILAB Approved no  
  Call Number Admin @ si @ CBC2013 Serial 2258  
Permanent link to this record
 

 
Author Debora Gil; Aura Hernandez-Sabate; Oriol Rodriguez; J. Mauri; Petia Radeva edit   pdf
doi  openurl
  Title (down) Statistical Strategy for Anisotropic Adventitia Modelling in IVUS Type Journal Article
  Year 2006 Publication IEEE Transactions on Medical Imaging Abbreviated Journal  
  Volume 25 Issue 6 Pages 768-778  
  Keywords Corners; T-junctions; Wavelets  
  Abstract Vessel plaque assessment by analysis of intravascular ultrasound sequences is a useful tool for cardiac disease diagnosis and intervention. Manual detection of luminal (inner) and mediaadventitia (external) vessel borders is the main activity of physicians in the process of lumen narrowing (plaque) quantification. Difficult definition of vessel border descriptors, as well as, shades, artifacts, and blurred signal response due to ultrasound physical properties trouble automated adventitia segmentation. In order to efficiently approach such a complex problem, we propose blending advanced anisotropic filtering operators and statistical classification techniques into a vessel border modelling strategy. Our systematic statistical analysis shows that the reported adventitia detection achieves an accuracy in the range of interobserver variability regardless of plaque nature, vessel geometry, and incomplete vessel borders. Index Terms–-Anisotropic processing, intravascular ultrasound (IVUS), vessel border segmentation, vessel structure classification.  
  Address  
  Corporate Author Thesis  
  Publisher 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 IAM;MILAB Approved no  
  Call Number IAM @ iam @ GHR2006 Serial 1525  
Permanent link to this record
 

 
Author Lluis Pere de las Heras; Ahmed Sheraz; Marcus Liwicki; Ernest Valveny; Gemma Sanchez edit   pdf
doi  openurl
  Title (down) Statistical Segmentation and Structural Recognition for Floor Plan Interpretation Type Journal Article
  Year 2014 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR  
  Volume 17 Issue 3 Pages 221-237  
  Keywords  
  Abstract A generic method for floor plan analysis and interpretation is presented in this article. The method, which is mainly inspired by the way engineers draw and interpret floor plans, applies two recognition steps in a bottom-up manner. First, basic building blocks, i.e., walls, doors, and windows are detected using a statistical patch-based segmentation approach. Second, a graph is generated, and structural pattern recognition techniques are applied to further locate the main entities, i.e., rooms of the building. The proposed approach is able to analyze any type of floor plan regardless of the notation used. We have evaluated our method on different publicly available datasets of real architectural floor plans with different notations. The overall detection and recognition accuracy is about 95 %, which is significantly better than any other state-of-the-art method. Our approach is generic enough such that it could be easily adopted to the recognition and interpretation of any other printed machine-generated structured documents.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1433-2833 ISBN Medium  
  Area Expedition Conference  
  Notes DAG; ADAS; 600.076; 600.077 Approved no  
  Call Number HSL2014 Serial 2370  
Permanent link to this record
 

 
Author Jaume Garcia edit   pdf
openurl 
  Title (down) Statistical Models of the Architecture and Function of the Left Ventricle Type Book Whole
  Year 2009 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Cardiovascular Diseases, specially those affecting the Left Ventricle (LV), are the leading cause of death in developed countries with approximately a 30% of all global deaths. In order to address this public health concern, physicians focus on diagnosis and therapy planning. On one hand, early and accurate detection of Regional Wall Motion Abnormalities (RWMA) significantly contributes to a quick diagnosis and prevents the patient to reach more severe stages. On the other hand, a thouroughly knowledge of the normal gross anatomy of the LV, as well as, the distribution of its muscular fibers is crucial for designing specific interventions and therapies (such as pacemaker implanction). Statistical models obtained from the analysis of different imaging modalities allow the computation of the normal ranges of variation within a given population. Normality models are a valuable tool for the definition of objective criterions quantifying the degree of (anomalous) deviation of the LV function and anatomy for a given subject. The creation of statistical models involve addressing three main issues: extraction of data from images, definition of a common domain for comparison of data across patients and designing appropriate statistical analysis schemes. In this PhD thesis we present generic image processing tools for the creation of statistical models of the LV anatomy and function. On one hand, we use differential geometry concepts to define a computational framework (the Normalized Parametric Domain, NPD) suitable for the comparison and fusion of several clinical scores obtained over the LV. On the other hand, we present a variational approach (the Harmonic Phase Flow, HPF) for the estimation of myocardial motion that provides dense and continuous vector fields without overestimating motion at injured areas. These tools are used for the creation of statistical models. Regarding anatomy, we obtain an atlas jointly modelling, both, LV gross anatomy and fiber architecture. Regarding function, we compute normality patterns of scores characterizing the (global and local) LV function and explore, for the first time, the configuration of local scores better suited for RWMA detection.  
  Address  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Debora Gil  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM Approved no  
  Call Number IAM @ iam @ Gar2009a Serial 1499  
Permanent link to this record
 

 
Author Thomas B. Moeslund; Sergio Escalera; Gholamreza Anbarjafari; Kamal Nasrollahi; Jun Wan edit  url
openurl 
  Title (down) Statistical Machine Learning for Human Behaviour Analysis Type Journal Article
  Year 2020 Publication Entropy Abbreviated Journal ENTROPY  
  Volume 25 Issue 5 Pages 530  
  Keywords action recognition; emotion recognition; privacy-aware  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher 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; no proj Approved no  
  Call Number Admin @ si @ MEA2020 Serial 3441  
Permanent link to this record
 

 
Author David Guillamet edit  openurl
  Title (down) Statistical Local Appearance Models for Object Recognition Type Book Whole
  Year 2004 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Bellaterra  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Place of Publication Editor Jordi Vitria  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number Admin @ si @ Gui2004 Serial 444  
Permanent link to this record
 

 
Author Jose Antonio Rodriguez edit  openurl
  Title (down) Statistical frameworks and prior information modeling in handwritten word-spotting Type Book Whole
  Year 2009 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Handwritten word-spotting (HWS) is the pattern analysis task that consists in finding keywords in handwritten document images. So far, HWS has been applied mostly to historical documents in order to build search engines for such image collections. This thesis addresses the problem of word-spotting for detecting important keywords in business documents. This is a first step towards the process of automatic routing of correspondence based on content.

However, the application of traditional HWS techniques fails for this type of documents. As opposed to historical documents, real business documents present a very high variability in terms of writing styles, spontaneous writing, crossed-out words, spelling mistakes, etc. The main goal of this thesis is the development of pattern recognition techniques that lead to a high-performance HWS system for this challenging type of data.

We develop a statistical framework in which word models are expressed in terms of hidden Markov models and the a priori information is encoded in a universal vocabulary of Gaussian codewords. This systems leads to a very robust performance in word-spotting task. We also find that by constraining the word models to the universal vocabulary, the a priori information of the problem of interest can be exploited for developing new contributions. These include a novel writer adaptation method, a system for searching handwritten words by generating typed text images, and a novel model-based similarity between feature vector sequences.
 
  Address Barcelona (Spain)  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Gemma Sanchez;Josep Llados;Florent Perronnin  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number Admin @ si @ Rod2009 Serial 1266  
Permanent link to this record
 

 
Author Debora Gil; Oriol Rodriguez; J. Mauri; Petia Radeva edit  openurl
  Title (down) Statistical descriptors of the Myocardial perfusion in angiographic images Type Conference Article
  Year 2006 Publication Proc. Computers in Cardiology Abbreviated Journal  
  Volume Issue Pages 677-680  
  Keywords Anisotropic processing; intravascular ultrasound (IVUS); vessel border segmentation; vessel structure classification.  
  Abstract Restoration of coronary flow after primary percutaneous coronary intervention in acute myocardial infarction does not always correlate with adequate myocardial perfusion. Recently, coronary angiography has been used to assess microcirculation integrity (Myocardial BlushAnalysis, MBA). Although MBA correlates with patient prognosis there are few image processing methods addressing objective perfusion quantification. The goal of this work is to develop statistical descriptors of the myocardial dyeing pattern allowing objective assessment of myocardial perfusion. Experiments on healthy right coronary arteries show that our approach allows reliable measurements without any specific image acquisition protocol.  
  Address  
  Corporate Author Thesis  
  Publisher 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 IAM;MILAB Approved no  
  Call Number IAM @ iam @ GRR2006 Serial 1528  
Permanent link to this record
 

 
Author Robert Benavente; Francesc Tous; Ramon Baldrich; Maria Vanrell edit  openurl
  Title (down) Statical Modelling of a Colour Naming Space. Type Miscellaneous
  Year 2002 Publication Proceedings of the 1st. European Conference on Colour in Graphics Imaging and Vision: 406–411. Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher 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 CIC Approved no  
  Call Number CAT @ cat @ BTB2002 Serial 289  
Permanent link to this record
 

 
Author Frederic Sampedro; Anna Domenech; Sergio Escalera edit  url
doi  openurl
  Title (down) Static and dynamic computational cancer spread quantification in whole body FDG-PET/CT scans Type Journal Article
  Year 2014 Publication Journal of Medical Imaging and Health Informatics Abbreviated Journal JMIHI  
  Volume 4 Issue 6 Pages 825-831  
  Keywords CANCER SPREAD; COMPUTER AIDED DIAGNOSIS; MEDICAL IMAGING; TUMOR QUANTIFICATION  
  Abstract In this work we address the computational cancer spread quantification scenario in whole body FDG-PET/CT scans. At the static level, this setting can be modeled as a clustering problem on the set of 3D connected components of the whole body PET tumoral segmentation mask carried out by nuclear medicine physicians. At the dynamic level, and ad-hoc algorithm is proposed in order to quantify the cancer spread time evolution which, when combined with other existing indicators, gives rise to the metabolic tumor volume-aggressiveness-spread time evolution chart, a novel tool that we claim that would prove useful in nuclear medicine and oncological clinical or research scenarios. Good performance results of the proposed methodologies both at the clinical and technological level are shown using a dataset of 48 segmented whole body FDG-PET/CT scans.  
  Address  
  Corporate Author Thesis  
  Publisher 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 @ SDE2014b Serial 2548  
Permanent link to this record
 

 
Author David Geronimo; Frederic Lerasle; Antonio Lopez edit   pdf
openurl 
  Title (down) State-driven particle filter for multi-person tracking Type Conference Article
  Year 2012 Publication 11th International Conference on Advanced Concepts for Intelligent Vision Systems Abbreviated Journal  
  Volume 7517 Issue Pages 467-478  
  Keywords human tracking  
  Abstract Multi-person tracking can be exploited in applications such as driver assistance, surveillance, multimedia and human-robot interaction. With the help of human detectors, particle filters offer a robust method able to filter noisy detections and provide temporal coherence. However, some traditional problems such as occlusions with other targets or the scene, temporal drifting or even the lost targets detection are rarely considered, making the systems performance decrease. Some authors propose to overcome these problems using heuristics not explained
and formalized in the papers, for instance by defining exceptions to the model updating depending on tracks overlapping. In this paper we propose to formalize these events by the use of a state-graph, defining the current state of the track (e.g., potential , tracked, occluded or lost) and the transitions between states in an explicit way. This approach has the advantage of linking track actions such as the online underlying models updating, which gives flexibility to the system. It provides an explicit representation to adapt the multiple parallel trackers depending on the context, i.e., each track can make use of a specific filtering strategy, dynamic model, number of particles, etc. depending on its state. We implement this technique in a single-camera multi-person tracker and test
it in public video sequences.
 
  Address Brno, Chzech Republic  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Heidelberg Editor J. Blanc-Talon et al.  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ACIVS  
  Notes ADAS Approved yes  
  Call Number GLL2012; ADAS @ adas @ gll2012a Serial 1990  
Permanent link to this record
 

 
Author Simone Balocco; Carlo Gatta; Francesco Ciompi; A. Wahle; Petia Radeva; S. Carlier; G. Unal; E. Sanidas; J. 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 (down) 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 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.
 
  Address  
  Corporate Author Thesis  
  Publisher 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 MILAB; LAMP; HuPBA; 600.046; 600.063; 600.079 Approved no  
  Call Number Admin @ si @ BGC2013 Serial 2314  
Permanent link to this record
 

 
Author Alicia Fornes; Josep Llados; Gemma Sanchez edit  openurl
  Title (down) Staff and graphical primitive segmentation in old handwritten music scores Type Miscellaneous
  Year 2005 Publication Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher 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 DAG Approved no  
  Call Number DAG @ dag @ FLS2005b Serial 585  
Permanent link to this record
 

 
Author Andres Mafla; Rafael S. Rezende; Lluis Gomez; Diana Larlus; Dimosthenis Karatzas edit   pdf
doi  openurl
  Title (down) StacMR: Scene-Text Aware Cross-Modal Retrieval Type Conference Article
  Year 2021 Publication IEEE Winter Conference on Applications of Computer Vision Abbreviated Journal  
  Volume Issue Pages 2219-2229  
  Keywords  
  Abstract  
  Address Virtual; January 2021  
  Corporate Author Thesis  
  Publisher 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 WACV  
  Notes DAG; 600.121 Approved no  
  Call Number Admin @ si @ MRG2021a Serial 3492  
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