Surgical Planning Laboratory - Brigham & Women's Hospital - Boston, Massachusetts USA - a teaching affiliate of Harvard Medical School

Surgical Planning Laboratory

The Publication Database hosted by SPL

All Publications | Upload | Advanced Search | Gallery View | Download Statistics | Help | Import | Log in

Group-wise Shape Correspondence of Variable and Complex Objects

1EECS, Vanderbilt University, Nashville, TN, USA.
2Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA.
3Department of Evolutionary Anthropology, Duke University, Durham, NC, USA.
4Kitware Inc., Carrboro, NC, USA.
Publication Date:
Proc SPIE Int Soc Opt Eng
Volume Number:
Proc SPIE Int Soc Opt Eng. 2018 Mar;10574.
PubMed ID:
Appears in Collections:
R01 EB021391/EB/NIBIB NIH HHS/United States
U54 EB005149/EB/NIBIB NIH HHS/United States
U54 HD079124/HD/NICHD NIH HHS/United States
P30 HD003110/HD/NICHD NIH HHS/United States
R01 MH070890/MH/NIMH NIH HHS/United States
R01 HD053000/HD/NICHD NIH HHS/United States
R01 MH091645/MH/NIMH NIH HHS/United States
Generated Citation:
Lyu I., Perdomo J., Yapuncich G.S., Paniagua B., Boyer D.M., Styner M.A. Group-wise Shape Correspondence of Variable and Complex Objects. Proc SPIE Int Soc Opt Eng. 2018 Mar;10574. PMID: 30381780. PMCID: PMC6205236.
Downloaded: 304 times. [view map]
Paper: Download, View online
Export citation:
Google Scholar: link

We present a group-wise shape correspondence method for analyzing variable and complex objects in a population study. The proposed method begins with the standard spherical harmonics (SPHARM) point distribution models (PDM) with their spherical mappings. In case of complex and variable objects, the equal area spherical mapping based SPHARM correspondence is imperfect. For such objects, we present here a novel group-wise correspondence. As an example dataset, we use 12 second mandibular molars representing 6 living or fossil euarchontan species. To improve initial correspondence of the SPHARM-PDM representation, we first apply a rigid transformation on each subject using five well-known landmarks (molar cusps). We further enhance the correspondence by optimizing landmarks (local) and multidimensional geometric property (global) over each subject with spherical harmonic representation. The resulting average shape model better captures sharp landmark representation in quantitative evaluation as well as a nice separation of different species compared with that of the SPHARM-PDM method.