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Title page for ETD etd-03292007-001623


Type of Document Dissertation
Author Laing, Christian Edgar
Author's Email Address claing@math.fsu.edu
URN etd-03292007-001623
Title Biomedical Applications of Shape Descriptors
Degree Doctor of Philosophy
Department Mathematics, Department of
Advisory Committee
Advisor Name Title
De Witt Sumners Committee Chair
Monica Hurdal Committee Member
Nancy Greenbaum Committee Member
Washington Mio Committee Member
Keywords
  • Bioclassification Database
  • Writhe
  • Lattices
  • RNA Classification
  • Brain Classification
Date of Defense 2007-03-12
Availability unrestricted
Abstract
Given an edge-oriented polygonal graph in R3, we describe a method for computing the writhe as the average of weighted directional writhe numbers of the graph in a few directions. These directions are determined by the graph and the weights are determined by areas of path-connected open regions on the unit sphere. Within each open region, the directional writhe is constant. We developed formulas for the writhe of polygons on Bravais lattices and a few crystallographic groups, and discuss applications to ring polymers. In addition, we obtained a closed formula for the writhe for graphs which extends the formula for the writhe of a polygon in R3, including the important special case of writhe of embedded open arcs. Additionally, we have developed shape descriptors based on a family of geometric measures for the purpose of classification and identification of shape differences for graphs. These shape descriptors involve combinations of writhe and average crossing numbers of curves, as well as total curvature, ropelength and thickness.

We have applied these shape descriptors to RNA tertiary structures and families of sulcal curves from human brain surfaces. Preliminary results give an automatic method to distinguish RNA motifs. Clear differentiation among tRNA and/or ribozymes, and a distinction among mesophilic and thermophilic tRNA is shown. In addition, we notice a direct correlation between the length of an RNA backbone and its mean average crossing number which is described accurately by a power function. As a neuroscience application, human brain surfaces were extracted from MRI scans of human brains. In our preliminary results, an automatic differentiation between sulcal paths from the left or right hemispheres, an age differentiation and a male-female classification were achieved.

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