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Author Sergio Vera; Debora Gil; Agnes Borras; F. Javier Sanchez; Frederic Perez; Marius G. Linguraru; Miguel Angel Gonzalez Ballester edit   pdf
doi  isbn
openurl 
  Title Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs Type Book Chapter
  Year 2012 Publication (down) Workshop on Computational and Clinical Applications in Abdominal Imaging Abbreviated Journal  
  Volume 7029 Issue Pages 223–230  
  Keywords medial manifolds, abdomen.  
  Abstract Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D
objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial
manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our
method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs,
exploring the use of medial manifolds for the representation of multi-organ relations.
 
  Address Toronto; Canada;  
  Corporate Author Thesis  
  Publisher Springer Link Place of Publication Berlin Editor H. Yoshida et al  
  Language English Summary Language English Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-28556-1 Medium  
  Area Expedition Conference ABDI  
  Notes IAM;MV Approved no  
  Call Number IAM @ iam @ VGB2012 Serial 1834  
Permanent link to this record
 

 
Author Hanne Kause; Aura Hernandez-Sabate; Patricia Marquez; Andrea Fuster; Luc Florack; Hans van Assen; Debora Gil edit   pdf
doi  isbn
openurl 
  Title Confidence Measures for Assessing the HARP Algorithm in Tagged Magnetic Resonance Imaging Type Book Chapter
  Year 2015 Publication (down) 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 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 Jaume Garcia; Debora Gil; Aura Hernandez-Sabate edit   pdf
doi  openurl
  Title Endowing Canonical Geometries to Cardiac Structures Type Book Chapter
  Year 2010 Publication (down) Statistical Atlases And Computational Models Of The Heart Abbreviated Journal  
  Volume 6364 Issue Pages 124-133  
  Keywords  
  Abstract International conference on Cardiac electrophysiological simulation challenge
In this paper, we show that canonical (shape-based) geometries can be endowed to cardiac structures using tubular coordinates defined over their medial axis. We give an analytic formulation of these geometries by means of B-Splines. Since B-Splines present vector space structure PCA can be applied to their control points and statistical models relating boundaries and the interior of the anatomical structures can be derived. We demonstrate the applicability in two cardiac structures, the 3D Left Ventricular volume, and the 2D Left-Right ventricle set in 2D Short Axis view.
 
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin / Heidelberg Place of Publication Editor Camara, O.; Pop, M.; Rhode, K.; Sermesant, M.; Smith, N.; Young, A.  
  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 Medium  
  Area Expedition Conference  
  Notes IAM Approved no  
  Call Number IAM @ iam @ GGH2010b Serial 1515  
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Author H. Martin ; Jens Fagertun; Sergio Vera; Debora Gil edit   pdf
openurl 
  Title Medial structure generation for registration of anatomical structures Type Book Chapter
  Year 2017 Publication (down) Skeletonization, Theory, Methods and Applications Abbreviated Journal  
  Volume 11 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 IAM; 600.096; 600.075; 600.145 Approved no  
  Call Number Admin @ si @ MFV2017a Serial 2935  
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Author Jaume Garcia; Petia Radeva; Francesc Carreras edit   pdf
openurl 
  Title Combining Spectral and Active Shape methods to Track Tagged MRI Type Book Chapter
  Year 2004 Publication (down) Recent Advances in Artificial Intelligence Research and Development Abbreviated Journal  
  Volume Issue Pages 37-44  
  Keywords MR; tagged MR; ASM; LV segmentation; motion estimation.  
  Abstract Tagged magnetic resonance is a very usefull and unique tool that provides a complete local and global knowledge of the left ventricle (LV) motion. In this article we introduce a method capable of tracking and segmenting the LV. Spectral methods are applied in order to obtain the so called HARP images which encode information about movement and are the base for LV point-tracking. For segmentation we use Active Shapes (ASM) that model LV shape variation in order to overcome possible local misplacements of the boundary. We finally show experiments on both synthetic and real data which appear to be very promising.  
  Address  
  Corporate Author Thesis  
  Publisher IOS Press 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 CCIA  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ GRC2004 Serial 1488  
Permanent link to this record
 

 
Author Debora Gil; Petia Radeva edit   pdf
openurl 
  Title Inhibition of False Landmarks Type Book Chapter
  Year 2004 Publication (down) Recent Advances in Artificial Intelligence Research and Development Abbreviated Journal  
  Volume Issue Pages 233-244  
  Keywords  
  Abstract We argue that a corner detector should be based on the degree of continuity of the tangent vector to the image level sets, work on the image domain and need no assumptions on neither the image local structure nor the particular geometry of the corner/junction. An operator measuring the degree of differentiability of the projection matrix on the image gradient fulfills the above requirements. Its high sensitivity to changes in vector directions makes it suitable for landmark location in real images prone to need smoothing to reduce the impact of noise. Because using smoothing kernels leads to corner misplacement, we suggest an alternative fake response remover based on the receptive field inhibition of spurious details. The combination of both orientation discontinuity detection and noise inhibition produce our Inhibition Orientation Energy (IOE) landmark locator.  
  Address  
  Corporate Author Thesis  
  Publisher IOS Press Place of Publication Barcelona (Spain) Editor al, J.V. et  
  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 @ GiR2004a Serial 1533  
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Author Fernando Vilariño; Debora Gil; Petia Radeva edit   pdf
url  isbn
openurl 
  Title A Novel FLDA Formulation for Numerical Stability Analysis Type Book Chapter
  Year 2004 Publication (down) Recent Advances in Artificial Intelligence Research and Development Abbreviated Journal  
  Volume 113 Issue Pages 77-84  
  Keywords Supervised Learning; Linear Discriminant Analysis; Numerical Stability; Computer Vision  
  Abstract Fisher Linear Discriminant Analysis (FLDA) is one of the most popular techniques used in classification applying dimensional reduction. The numerical scheme involves the inversion of the within-class scatter matrix, which makes FLDA potentially ill-conditioned when it becomes singular. In this paper we present a novel explicit formulation of FLDA in terms of the eccentricity ratio and eigenvector orientations of the within-class scatter matrix. An analysis of this function will characterize those situations where FLDA response is not reliable because of numerical instability. This can solve common situations of poor classification performance in computer vision.  
  Address  
  Corporate Author Thesis  
  Publisher IOS Press Place of Publication Editor J. Vitrià, P. Radeva and I. Aguiló  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-58603-466-5 Medium  
  Area Expedition Conference  
  Notes MV;IAM;MILAB;SIAI Approved no  
  Call Number IAM @ iam @ VGR2004 Serial 1663  
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Author Debora Gil; Jordi Gonzalez; Gemma Sanchez (eds) edit  isbn
openurl 
  Title Computer Vision: Advances in Research and Development Type Book Whole
  Year 2007 Publication (down) Proceedings of the 2nd CVC International Workshop Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher UAB Place of Publication Bellaterra (Spain) Editor Debora Gil; Jordi Gonzalez; Gemma Sanchez  
  Language Summary Language Original Title  
  Series Editor Series Title 2 Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-84-935251-4-9 Medium  
  Area Expedition Conference  
  Notes IAM; ISE; DAG Approved no  
  Call Number IAM @ iam @ GGS2007 Serial 1493  
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Author Jaume Garcia edit   pdf
openurl 
  Title Statistical Models of the Architecture and Function of the Left Ventricle Type Book Whole
  Year 2009 Publication (down) 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 Debora Gil edit   pdf
isbn  openurl
  Title Geometric Differential Operators for Shape Modelling Type Book Whole
  Year 2004 Publication (down) PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Medical imaging feeds research in many computer vision and image processing fields: image filtering, segmentation, shape recovery, registration, retrieval and pattern matching. Because of their low contrast changes and large variety of artifacts and noise, medical imaging processing techniques relying on an analysis of the geometry of image level sets rather than on intensity values result in more robust treatment. From the starting point of treatment of intravascular images, this PhD thesis ad- dresses the design of differential image operators based on geometric principles for a robust shape modelling and restoration. Among all fields applying shape recovery, we approach filtering and segmentation of image objects. For a successful use in real images, the segmentation process should go through three stages: noise removing, shape modelling and shape recovery. This PhD addresses all three topics, but for the sake of algorithms as automated as possible, techniques for image processing will be designed to satisfy three main principles: a) convergence of the iterative schemes to non-trivial states avoiding image degeneration to a constant image and representing smooth models of the originals; b) smooth asymptotic behav- ior ensuring stabilization of the iterative process; c) fixed parameter values ensuring equal (domain free) performance of the algorithms whatever initial images/shapes. Our geometric approach to the generic equations that model the different processes approached enables defining techniques satisfying all the former requirements. First, we introduce a new curvature-based geometric flow for image filtering achieving a good compromise between noise removing and resemblance to original images. Sec- ond, we describe a new family of diffusion operators that restrict their scope to image level curves and serve to restore smooth closed models from unconnected sets of points. Finally, we design a regularization of snake (distance) maps that ensures its smooth convergence towards any closed shape. Experiments show that performance of the techniques proposed overpasses that of state-of-the-art algorithms.  
  Address  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Barcelona (Spain) Editor Jordi Saludes i Closa;Petia Radeva  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 84-933652-0-3 Medium prit  
  Area Expedition Conference  
  Notes IAM; Approved no  
  Call Number IAM @ iam @ GIL2004 Serial 1517  
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