A fast mesh deformation method for neuroanatomical surface inflated representations

Andrea Rueda, Álvaro Perea, Daniel Rodríguez-Pérez, Eduardo Romero

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Resumen

In this paper we present a new metric preserving deformation method which permits to generate smoothed representations of neuroanatomical structures. These surfaces are approximated by triangulated meshes which are evolved using an external velocity field, modified by a local curvature dependent contribution. This motion conserves local metric properties since the external force is modified by explicitely including an area preserving term into the motion equation. We show its applicability by computing inflated representations from real neuroanatomical data and obtaining smoothed surfaces whose local area distortion is less than a 5 %, when comparing with the original ones.

Idioma originalInglés
Título de la publicación alojadaAdvances in Image and Video Technology - Second Pacific Rim Symposium, PSIVT 2007, Proceedings
EditorialSpringer Verlag
Páginas75-86
Número de páginas12
ISBN (versión impresa)9783540771289
DOI
EstadoPublicada - 2007
Publicado de forma externa
Evento2nd Pacific Rim Symposium on Image and Video Technology, PSIVT 2007 - Santiago, Chile
Duración: 17 dic. 200719 dic. 2007

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen4872 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia2nd Pacific Rim Symposium on Image and Video Technology, PSIVT 2007
País/TerritorioChile
CiudadSantiago
Período17/12/0719/12/07

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