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On the Adequacy of Principal Factor Analysis for the Study of Shape Variability
 

Summary: On the Adequacy of Principal Factor Analysis for the Study
of Shape Variability
Miguel ´Angel Gonz´alez Ballestera,b, Marius George Lingurarub,c,
Mauricio Reyes Aguirreb and Nicholas Ayacheb
a University of Bern, MEM Research Center,
Institute for Surgical Technology and Biomechanics,
Stauffacherstrasse 78, CH-3014 Bern, Switzerland
http://memcenter.unibe.ch
b INRIA, Epidaure Research Project,
2004 route des lucioles BP 93, Sophia Antipolis, 06902 France
http://www.inria.fr/epidaure
c Harvard University, Biorobotics Laboratory,
29 Oxford Street, Cambridge MA 02138, USA
http://biorobotics.harvard.edu
ABSTRACT
The analysis of shape variability of anatomical structures is of key importance in a number of clinical disciplines,
as abnormality in shape can be related to certain diseases. Statistical shape analysis techniques commonly
employed in the medical imaging community, such as Active Shape Models or Active Appearance Models rely
on Principal Component Analysis (PCA) to decompose shape variability into a reduced set of interpretable
components. In this paper we propose Principal Factor Analysis (PFA) as an alternative to PCA and argue

  

Source: Ayache, Nicholas - INRIA

 

Collections: Computer Technologies and Information Sciences; Engineering