This dissertation studies two problems related to geometric representation of
neuroanatomical data: (i) spatial representation and organization of individual neurons,
and (ii) reconstruction of three-dimensional neuroanatomical regions from sparse two-dimensional
drawings. This work has been motivated by nearby development of new
technology, Knife-Edge Scanning Microscopy (KESM), that images a whole mouse
brain at cellular level in less than a month.
A method is introduced to represent neuronal data observed in the mammalian brain at
the cellular level using geometric primitives and spatial indexing. A data representation
scheme is defined that captures the geometry of individual neurons using traditional
geometric primitives, points and cross-sectional areas along a trajectory. This
representation captures inferred synapses as directed links between primitives and
spatially indexes observed neurons based on the locations of their cell bodies. This
method provides a set of rules for acquisition, representation, and indexing of KESMgenerated
data.
Neuroanatomical data observed at the gross level provides the underlying regional
framework for neuronal circuits. Accumulated expert knowledge on neuroanatomical organization is usually given as a series of sparse two-dimensional contours. A data
structure and an algorithm are described to reconstruct separating surfaces among
multiple regions from these sparse cross-sectional contours. A topology graph is defined
for each region that describes the topological skeleton of the region’s boundary surface
and that shows between which contours the surface patches should be generated. A
graph-directed triangulation algorithm is provided to reconstruct surface patches
between contours. This graph-directed triangulation algorithm combined together with
a piecewise parametric curve fitting technique ensures that abutting or shared surface
patches are precisely coincident. This method overcomes limitations in i) traditional
surfaces-from-contours algorithms that assume binary, not multiple, regionalization of
space, and in ii) few existing separating surfaces algorithms that assume conversion of
input into a regular volumetric grid, which is not possible with sparse inter-planar
resolution.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-1669 |
| Date | 15 May 2009 |
| Creators | Koh, Wonryull |
| Contributors | McCormick, Bruce H. |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | electronic, application/pdf, born digital |
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