Publicacions CVC -- Query Results

<< 1 2 3 4 >>

Details

	Records
	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
Permanent link to this record

Select All Deselect All

<< 1 2 3 4 >>

List View

Citations

Details

All Found Records Selected Records:

Save Citations: Format:

Export Records: Format: