Wavelet-based representation of biological shapes

Bin Dong, Yu Mao, Ivo D. Dinov, Zhuowen Tu, Yonggang Shi, Yalin Wang, Arthur W. Toga

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


Modeling, characterization and analysis of biological shapes and forms are important in many computational biology studies. Shape representation challenges span the spectrum from small scales (e.g., microarray imaging and protein structure) to the macro scale (e.g., neuroimaging of human brains). In this paper, we present a new approach to represent and analyze biological shapes using wavelets. We apply the new technique to multi-spectral shape decomposition and study shape variability between populations using brain cortical and subcortical surfaces. The wavelet-space-induced shape representation allows us to study the multi-spectral nature of the shape's geometry, topology and features. Our results are very promising and, comparing to the spherical-wavelets method, our approach is more compact and allows utilization of diverse wavelet bases.

Original languageEnglish (US)
Title of host publicationAdvances in Visual Computing - 5th International Symposium, ISVC 2009, Proceedings
Number of pages10
EditionPART 1
StatePublished - 2009
Externally publishedYes
Event5th International Symposium on Advances in Visual Computing, ISVC 2009 - Las Vegas, NV, United States
Duration: Nov 30 2009Dec 2 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5875 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other5th International Symposium on Advances in Visual Computing, ISVC 2009
Country/TerritoryUnited States
CityLas Vegas, NV

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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