Functional data analysis in shape analysis
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Título
Functional data analysis in shape analysisFecha de publicación
2011Editor
ElsevierISSN
0167-9473Tipo de documento
info:eu-repo/semantics/articleVersión
info:eu-repo/semantics/submittedVersionPalabras clave / Materias
Resumen
Mid-level processes on images often return outputs in functional form. In
this context the use of functional data analysis (FDA) in image analysis is
considered. In particular, attention is focussed on shape analysis, ... [+]
Mid-level processes on images often return outputs in functional form. In
this context the use of functional data analysis (FDA) in image analysis is
considered. In particular, attention is focussed on shape analysis, where the
use of FDA in the functional approach (contour functions) shows its superiority
over other approaches, such as the landmark based approach or the
set theory approach, on two different problems (principal component analysis
and discriminant analysis) in a well-known database of bone outlines.
Furthermore, a problem that has hardly ever been considered in the literature
is dealt with: multivariate functional discrimination. A discriminant
function based on independent component analysis for indicating where the
differences between groups are and what their level of discrimination is, is
proposed. The classification results obtained with the methodology are very
promising. Finally, an analysis of hippocampal differences in Alzheimer’s
disease is carried out. [-]
Publicado en
Computational Statistics & Data Analysis, vol. 55, n. 9, p. 2758-2773 (2011)Derechos de acceso
http://rightsstatements.org/vocab/CNE/1.0/
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
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