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Combined SPHARM-PDM and Entropy-based Particle Systems Shape Analysis Framework

1Department of Psychiatry, University of North Carolina at Chapel Hill, NC, USA.
2Scientific Computing Institute, University of Utah, Salt Lake City, UT, USA.
Publication Date:
Proc SPIE. 2012 Mar 23; 8317: 83170L.
PubMed ID:
Spherical harmonic representation, entropy-based particle systems, statistical shape analysis, shape analysis framework, 3D Slicer
Appears in Collections:
U54 EB005149/EB/NIBIB NIH HHS/United States
P30 HD003110/HD/NICHD NIH HHS/United States
RC1 AA019211/AA/NIAAA NIH HHS/United States
P50 MH064065/MH/NIMH NIH HHS/United States
R01 MH061696/MH/NIMH NIH HHS/United States
R01 MH064580/MH/NIMH NIH HHS/United States
Generated Citation:
Paniagua B., Bompard L., Cates J., Whitaker R., Datar M., Vachet C., Styner M. Combined SPHARM-PDM and Entropy-based Particle Systems Shape Analysis Framework. Proc SPIE. 2012 Mar 23; 8317: 83170L. PMID: 24027625. PMCID: PMC3766973.
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The NA-MIC SPHARM-PDM Toolbox represents an automated set of tools for the computation of 3D structural statistical shape analysis. SPHARM-PDM solves the correspondence problem by defining a first order ellipsoid aligned, uniform spherical parameterization for each object with correspondence established at equivalently parameterized points. However, SPHARM correspondence has shown to be inadequate for some biological shapes that are not well described by a uniform spherical parameterization. Entropy-based particle systems compute correspondence by representing surfaces as discrete point sets that does not rely on any inherent parameterization. However, they are sensitive to initialization and have little ability to recover from initial errors. By combining both methodologies we compute reliable correspondences in topologically challenging biological shapes.

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