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Author Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil
Title Optimal Medial Surface Generation for Anatomical Volume Representations Type Book Chapter
Year 2012 Publication Abdominal Imaging. Computational and Clinical Applications Abbreviated Journal LNCS
Volume 7601 Issue Pages 265-273
Keywords Medial surface representation; volume reconstruction
Abstract Medial representations are a widely used technique in abdominal organ shape representation and parametrization. Those methods require good medial manifolds as a starting point. Any medial
surface used to parametrize a volume should be simple enough to allow an easy manipulation and complete enough to allow an accurate reconstruction of the volume. Obtaining good quality medial
surfaces is still a problem with current iterative thinning methods. This forces the usage of generic, pre-calculated medial templates that are adapted to the final shape at the cost of a drop in volume reconstruction.
This paper describes an operator for generation of medial structures that generates clean and complete manifolds well suited for their further use in medial representations of abdominal organ volumes. While being simpler than thinning surfaces, experiments show its high performance in volume reconstruction and preservation of medial surface main branching topology.
Address Nice, France
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor Yoshida, Hiroyuki and Hawkes, David and Vannier, MichaelW.
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-33611-9 Medium
Area Expedition Conference (down) STACOM
Notes IAM Approved no
Call Number IAM @ iam @ VGG2012b Serial 1988
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Author Hanne Kause; Aura Hernandez-Sabate; Patricia Marquez; Andrea Fuster; Luc Florack; Hans van Assen; Debora Gil
Title Confidence Measures for Assessing the HARP Algorithm in Tagged Magnetic Resonance Imaging Type Book Chapter
Year 2015 Publication Statistical Atlases and Computational Models of the Heart. Revised selected papers of Imaging and Modelling Challenges 6th International Workshop, STACOM 2015, Held in Conjunction with MICCAI 2015 Abbreviated Journal
Volume 9534 Issue Pages 69-79
Keywords
Abstract Cardiac deformation and changes therein have been linked to pathologies. Both can be extracted in detail from tagged Magnetic Resonance Imaging (tMRI) using harmonic phase (HARP) images. Although point tracking algorithms have shown to have high accuracies on HARP images, these vary with position. Detecting and discarding areas with unreliable results is crucial for use in clinical support systems. This paper assesses the capability of two confidence measures (CMs), based on energy and image structure, for detecting locations with reduced accuracy in motion tracking results. These CMs were tested on a database of simulated tMRI images containing the most common artifacts that may affect tracking accuracy. CM performance is assessed based on its capability for HARP tracking error bounding and compared in terms of significant differences detected using a multi comparison analysis of variance that takes into account the most influential factors on HARP tracking performance. Results showed that the CM based on image structure was better suited to detect unreliable optical flow vectors. In addition, it was shown that CMs can be used to detect optical flow vectors with large errors in order to improve the optical flow obtained with the HARP tracking algorithm.
Address Munich; Germany; January 2015
Corporate Author Thesis
Publisher Springer International Publishing 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 978-3-319-28711-9 Medium
Area Expedition Conference (down) STACOM
Notes ADAS; IAM; 600.075; 600.076; 600.060; 601.145 Approved no
Call Number Admin @ si @ KHM2015 Serial 2734
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Author Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades
Title Spotting Symbol over Graphical Documents Via Sparsity in Visual Vocabulary Type Book Chapter
Year 2016 Publication Recent Trends in Image Processing and Pattern Recognition Abbreviated Journal
Volume 709 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 (down) RTIP2R
Notes DAG Approved no
Call Number Admin @ si @ HTR2016 Serial 2956
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Author Panagiota Spyridonos; Fernando Vilariño; Jordi Vitria; Fernando Azpiroz; Petia Radeva
Title Anisotropic Feature Extraction from Endoluminal Images for Detection of Intestinal Contractions Type Book Chapter
Year 2006 Publication 9th International Conference on Medical Image Computing and Computer–Assisted Intervention Abbreviated Journal
Volume 4191 Issue Pages 161–168
Keywords
Abstract Wireless endoscopy is a very recent and at the same time unique technique allowing to visualize and study the occurrence of con- tractions and to analyze the intestine motility. Feature extraction is es- sential for getting efficient patterns to detect contractions in wireless video endoscopy of small intestine. We propose a novel method based on anisotropic image filtering and efficient statistical classification of con- traction features. In particular, we apply the image gradient tensor for mining informative skeletons from the original image and a sequence of descriptors for capturing the characteristic pattern of contractions. Fea- tures extracted from the endoluminal images were evaluated in terms of their discriminatory ability in correct classifying images as either belong- ing to contractions or not. Classification was performed by means of a support vector machine classifier with a radial basis function kernel. Our classification rates gave sensitivity of the order of 90.84% and specificity of the order of 94.43% respectively. These preliminary results highlight the high efficiency of the selected descriptors and support the feasibility of the proposed method in assisting the automatic detection and analysis of contractions.
Address Copenhagen (Denmark)
Corporate Author Thesis
Publisher Springer Verlag Place of Publication Berlin Heidelberg Editor R. Larsen, M. Nielsen, and J. Sporring
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area 800 Expedition Conference (down) MICCAI06
Notes MV;OR;MILAB;SIAI Approved no
Call Number BCNPCL @ bcnpcl @ SVV2006; IAM @ iam @ SVV2006 Serial 725
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Author Carlo Gatta; Oriol Pujol; Oriol Rodriguez-Leor; J. Mauri; Petia Radeva
Title Robust Image-based IVUS Pullbacks Gating Type Book Chapter
Year 2008 Publication Proceedings 11th International ConferenceMedical Image Computing and Computer–Assisted Intervention Abbreviated Journal
Volume 5242 Issue Pages 518–525
Keywords
Abstract
Address NY (USA)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference (down) MICCAI
Notes MILAB;HuPBA Approved no
Call Number BCNPCL @ bcnpcl @ GPR2008a Serial 1037
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Author Santiago Segui; Laura Igual; Fernando Vilariño; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria
Title Diagnostic System for Intestinal Motility Disfunctions Using Video Capsule Endoscopy Type Book Chapter
Year 2008 Publication Computer Vision Systems. 6th International Abbreviated Journal
Volume 5008 Issue Pages 251–260
Keywords
Abstract Wireless Video Capsule Endoscopy is a clinical technique consisting of the analysis of images from the intestine which are pro- vided by an ingestible device with a camera attached to it. In this paper we propose an automatic system to diagnose severe intestinal motility disfunctions using the video endoscopy data. The system is based on the application of computer vision techniques within a machine learn- ing framework in order to obtain the characterization of diverse motil- ity events from video sequences. We present experimental results that demonstrate the effectiveness of the proposed system and compare them with the ground-truth provided by the gastroenterologists.
Address Santorini (Greece)
Corporate Author Thesis
Publisher Springer-Verlag Place of Publication Berlin Heidelberg Editor A. Gasteratos, M. Vincze, and J.K. Tsotsos
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-540-79546-9 Medium
Area 800 Expedition Conference (down) ICVS
Notes OR; MV; MILAB; SIAI Approved no
Call Number BCNPCL @ bcnpcl @ SIV2008; IAM @ iam @ SIV2008 Serial 962
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Author Sergio Escalera; Oriol Pujol; Petia Radeva
Title Sub-Class Error-Correcting Output Codes Type Book Chapter
Year 2008 Publication Computer Vision Systems. 6th International Conference Abbreviated Journal
Volume 5008 Issue Pages 494–504
Keywords
Abstract
Address Santorini (Greece)
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 (down) ICVS
Notes MILAB;HuPBA Approved no
Call Number BCNPCL @ bcnpcl @ EPR2008c Serial 963
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Author Bogdan Raducanu; Fadi Dornaika
Title A Discriminative Non-Linear Manifold Learning Technique for Face Recognition Type Book Chapter
Year 2011 Publication Informatics Engineering and Information Science Abbreviated Journal
Volume 254 Issue 6 Pages 339-353
Keywords
Abstract In this paper we propose a novel non-linear discriminative analysis technique for manifold learning. The proposed approach is a discriminant version of Laplacian Eigenmaps which takes into account the class label information in order to guide the procedure of non-linear dimensionality reduction. By following the large margin concept, the graph Laplacian is split in two components: within-class graph and between-class graph to better characterize the discriminant property of the data.
Our approach has been tested on several challenging face databases and it has been conveniently compared with other linear and non-linear techniques. The experimental results confirm that our method outperforms, in general, the existing ones. Although we have concentrated in this paper on the face recognition problem, the proposed approach could also be applied to other category of objects characterized by large variance in their appearance.
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 1865-0929 ISBN 978-3-642-25482-6 Medium
Area Expedition Conference (down) ICIEIS
Notes OR;MV Approved no
Call Number Admin @ si @ RaD2011 Serial 1804
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Author Carles Sanchez;F. Javier Sanchez; Antoni Rosell; Debora Gil
Title An illumination model of the trachea appearance in videobronchoscopy images Type Book Chapter
Year 2012 Publication Image Analysis and Recognition Abbreviated Journal LNCS
Volume 7325 Issue Pages 313-320
Keywords Bronchoscopy, tracheal ring, stenosis assesment, trachea appearance model, segmentation
Abstract Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways. This imaging modality provides realistic images and allows non-invasive minimal intervention procedures. Tracheal procedures are routinary interventions that require assessment of the percentage of obstructed pathway for injury (stenosis) detection. Visual assessment in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error.
This paper introduces an automatic method for the estimation of steneosed trachea percentage reduction in videobronchoscopic images. We look for tracheal rings , whose deformation determines the degree of obstruction. For ring extraction , we present a ring detector based on an illumination and appearance model. This model allows us to parametrise the ring detection. Finally, we can infer optimal estimation parameters for any video resolution.
Address Aveiro, Portugal
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-31297-7 Medium
Area 800 Expedition Conference (down) ICIAR
Notes MV;IAM Approved no
Call Number IAM @ iam @ SSR2012 Serial 1898
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Author Salim Jouili; Salvatore Tabbone; Ernest Valveny
Title Comparing Graph Similarity Measures for Graphical Recognition Type Book Chapter
Year 2010 Publication Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers Abbreviated Journal
Volume 6020 Issue Pages 37-48
Keywords
Abstract In this paper we evaluate four graph distance measures. The analysis is performed for document retrieval tasks. For this aim, different kind of documents are used including line drawings (symbols), ancient documents (ornamental letters), shapes and trademark-logos. The experimental results show that the performance of each graph distance measure depends on the kind of data and the graph representation technique.
Address
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 978-3-642-13727-3 Medium
Area Expedition Conference (down) GREC
Notes DAG Approved no
Call Number Admin @ si @ JTV2010 Serial 2404
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Author Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti
Title Symbol recognition: current advances and perspectives Type Book Chapter
Year 2002 Publication Graphics Recognition Algorithms And Applications Abbreviated Journal LNCS
Volume 2390 Issue Pages 104-128
Keywords
Abstract The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content.
Address London, UK
Corporate Author Thesis
Publisher Springer-Verlag Place of Publication Editor Dorothea Blostein and Young- Bin Kwon
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 3-540-44066-6 Medium
Area Expedition Conference (down) GREC
Notes DAG; IAM; Approved no
Call Number IAM @ iam @ LVS2002 Serial 1572
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Author Joan Mas; Gemma Sanchez; Josep Llados
Title SSP: Sketching slide Presentations, a Syntactic Approach Type Book Chapter
Year 2010 Publication Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers Abbreviated Journal
Volume 6020 Issue Pages 118-129
Keywords
Abstract The design of a slide presentation is a creative process. In this process first, humans visualize in their minds what they want to explain. Then, they have to be able to represent this knowledge in an understandable way. There exists a lot of commercial software that allows to create our own slide presentations but the creativity of the user is rather limited. In this article we present an application that allows the user to create and visualize a slide presentation from a sketch. A slide may be seen as a graphical document or a diagram where its elements are placed in a particular spatial arrangement. To describe and recognize slides a syntactic approach is proposed. This approach is based on an Adjacency Grammar and a parsing methodology to cope with this kind of grammars. The experimental evaluation shows the performance of our methodology from a qualitative and a quantitative point of view. Six different slides containing different number of symbols, from 4 to 7, have been given to the users and they have drawn them without restrictions in the order of the elements. The quantitative results give an idea on how suitable is our methodology to describe and recognize the different elements in a slide.
Address
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 978-3-642-13727-3 Medium
Area Expedition Conference (down) GREC
Notes DAG Approved no
Call Number MSL2010 Serial 2405
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Author Mathieu Nicolas Delalandre; Jean-Yves Ramel; Ernest Valveny; Muhammad Muzzamil Luqman
Title A Performance Characterization Algorithm for Symbol Localization Type Book Chapter
Year 2010 Publication Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers Abbreviated Journal
Volume 6020 Issue Pages 260–271
Keywords
Abstract In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more “reliable” and “open” solution to characterize the performance. To achieve that, it exploits only single points as the result of localization and offers the possibility to reconsider the localization results provided by a system. We use the information about context in groundtruth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a groundtruth region, depending on the spatial distribution of the other regions in the groundtruth. Final characterization is given with detection rate/probability score plots, describing the sets of possible interpretations of the localization results, according to a given confidence rate. We present experimentation details along with the results for the symbol localization system of [1], exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols).
Address
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 978-3-642-13727-3 Medium
Area Expedition Conference (down) GREC
Notes DAG Approved no
Call Number Admin @ si @ DRV2010 Serial 2406
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Author Hana Jarraya; Muhammad Muzzamil Luqman; Jean-Yves Ramel
Title Improving Fuzzy Multilevel Graph Embedding Technique by Employing Topological Node Features: An Application to Graphics Recognition Type Book Chapter
Year 2017 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal
Volume 9657 Issue Pages
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Springer Place of Publication Editor B. Lamiroy; R Dueire Lins
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference (down) GREC
Notes DAG; 600.097; 600.121 Approved no
Call Number Admin @ si @ JLR2017 Serial 2928
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Author Arnau Baro; Pau Riba; Jorge Calvo-Zaragoza; Alicia Fornes
Title Optical Music Recognition by Long Short-Term Memory Networks Type Book Chapter
Year 2018 Publication Graphics Recognition. Current Trends and Evolutions Abbreviated Journal
Volume 11009 Issue Pages 81-95
Keywords Optical Music Recognition; Recurrent Neural Network; Long ShortTerm Memory
Abstract Optical Music Recognition refers to the task of transcribing the image of a music score into a machine-readable format. Many music scores are written in a single staff, and therefore, they could be treated as a sequence. Therefore, this work explores the use of Long Short-Term Memory (LSTM) Recurrent Neural Networks for reading the music score sequentially, where the LSTM helps in keeping the context. For training, we have used a synthetic dataset of more than 40000 images, labeled at primitive level. The experimental results are promising, showing the benefits of our approach.
Address
Corporate Author Thesis
Publisher Springer Place of Publication Editor A. Fornes, B. Lamiroy
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-030-02283-9 Medium
Area Expedition Conference (down) GREC
Notes DAG; 600.097; 601.302; 601.330; 600.121 Approved no
Call Number Admin @ si @ BRC2018 Serial 3227
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