A Fast Mesh Deformation Method for Neuroanatomical Surface Inflated Representations

  • Andrea Rueda
  • Álvaro Perea
  • Daniel Rodríguez-Pérez
  • Eduardo Romero
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4872)


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.


area-preserving deformation model deformable geometry surface inflating 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Andrea Rueda
    • 1
  • Álvaro Perea
    • 2
  • Daniel Rodríguez-Pérez
    • 2
  • Eduardo Romero
    • 1
  1. 1.BioIngenium Research Group, Universidad Nacional de Colombia, Carrera 30  45-03, BogotáColombia
  2. 2.Department of Mathematical Physics and Fluids, Universidad Nacional de Educación a Distancia, c/ Senda del Rey, 9, 28040 MadridSpain

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