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Abstract Details
Activity Number:
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649
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Type:
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Topic Contributed
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Date/Time:
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Thursday, August 4, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Nonparametric Statistics
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Abstract - #302908 |
Title:
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Medical Imaging Application: Nonparametric Statistics on 3D Size-and-Reflection Shape Manifold
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Author(s):
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Daniel Osborne*+ and Victor Patrangenaru and Xiuwen Liu and Hillary W. Thompson
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Companies:
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Florida State University and Florida State University and Florida State University and Louisiana State University
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Address:
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Department of Statistics, Tallahassee, FL, 32306, USA
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Keywords:
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Size-and-reflection shape ;
statistical methods in medical imaging ;
statistics on manifolds ;
extrinsic means ;
nonparametric bootstrap ;
confidence region
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Abstract:
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For medical imaging problems, nonparametric statistics on size-and-reflection shape space of k-ads in general position in 2D or 3D, is performed for purposes of diagnostics, discrimination, and/or identification. Here we focus on various steps of a larger collaborative project between researchers from Louisiana State and Florida State, on planning reconstructive neurosurgery for severe injuries of the skull. The pre-processing step consists of the extraction the boundary of the bone structure from the CT slices while the post-processing step consists of 3D reconstruction of the virtual skull from these bone extractions. Next, we present preliminary results for the Schoenberg sample mean size-and-reflection shape of groups of anatomic landmarks in general position in 3D for the human skull based on these virtual reconstructions. The bootstrap distribution of the Schoenberg's sample mean size-and-reflection shape for a selected group of k-ads ( landmarks and pseudo-landmarks ) was computed for 500 bootstrap resamples of the original 20 skulls represented by the 3 by k configurations, when k = 9, k = 17. Finally, we report a confidence region for the Schoenberg mean configuration.
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