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Author Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil edit   pdf
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  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 STACOM  
  Notes IAM Approved no  
  Call Number (up) IAM @ iam @ VGG2012b Serial 1988  
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Author Fernando Vilariño; Debora Gil; Petia Radeva edit   pdf
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  Title A Novel FLDA Formulation for Numerical Stability Analysis Type Book Chapter
  Year 2004 Publication 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 Approved no  
  Call Number (up) IAM @ iam @ VGR2004 Serial 1663  
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