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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
STACOM
Notes
IAM
Approved
no
Call Number
IAM @ iam @ VGG2012b
Serial
1988
Permanent link to this record
Author
Fernando Vilariño; Debora Gil; Petia Radeva
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
IAM @ iam @ VGR2004
Serial
1663
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