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Authors: Darwin Martínez 1 ; Isabelle Bloch 1 and Tiberio Hernández 2

Affiliations: 1 TELECOM ParisTech (ENST), France ; 2 Universidad Los Andes, Colombia

Keyword(s): Anatomical variability, MRI images, Brain structures, Principal component analysis.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Feature Extraction ; Features Extraction ; Image and Video Analysis ; Informatics in Control, Automation and Robotics ; Signal Processing, Sensors, Systems Modeling and Control ; Statistical Approach ; Surface Geometry and Shape

Abstract: In this paper we propose to analyze the variability of brain structures using principal component analysis (PCA). We rely on a data base of registered and segmented 3D MRI images of normal subjects. We propose to use as input of PCA sampled points on the surface of the considered objects, selected using uniformity criteria or based on mean and Gaussian curvatures. Results are shown on the lateral ventricles. The main variation tendencies are observed in the orthogonal eigenvector space. Dimensionality reduction can be achieved and the variability of each landmark point is accurately described using the first three components.

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Paper citation in several formats:
Martínez, D.; Bloch, I. and Hernández, T. (2009). ASSESSING THE VARIABILITY OF INTERNAL BRAIN STRUCTURES USING PCA ON SAMPLED SURFACE POINTS. In Proceedings of the Fourth International Conference on Computer Vision Theory and Applications (VISIGRAPP 2009) - Volume 2: VISAPP; ISBN 978-989-8111-69-2; ISSN 2184-4321, SciTePress, pages 172-179. DOI: 10.5220/0001790801720179

@conference{visapp09,
author={Darwin Martínez. and Isabelle Bloch. and Tiberio Hernández.},
title={ASSESSING THE VARIABILITY OF INTERNAL BRAIN STRUCTURES USING PCA ON SAMPLED SURFACE POINTS},
booktitle={Proceedings of the Fourth International Conference on Computer Vision Theory and Applications (VISIGRAPP 2009) - Volume 2: VISAPP},
year={2009},
pages={172-179},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001790801720179},
isbn={978-989-8111-69-2},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the Fourth International Conference on Computer Vision Theory and Applications (VISIGRAPP 2009) - Volume 2: VISAPP
TI - ASSESSING THE VARIABILITY OF INTERNAL BRAIN STRUCTURES USING PCA ON SAMPLED SURFACE POINTS
SN - 978-989-8111-69-2
IS - 2184-4321
AU - Martínez, D.
AU - Bloch, I.
AU - Hernández, T.
PY - 2009
SP - 172
EP - 179
DO - 10.5220/0001790801720179
PB - SciTePress