Segmentation strategies for polymerized volume data sets
| Title: | Segmentation strategies for polymerized volume data sets |
| Author: | Doddapaneni, Venkata Purna |
| Abstract: | A new technique, called the polymerization algorithm, is described for the hierarchical segmentation of polymerized volume data sets (PVDS) using the Lblock data structure. The Lblock data structure is defined as a 3dimensional isorectangular block of enhanced vertex information. Segmentation of the PVDS is attained by intersecting and merging Lblock coverings of the enhanced volumetric data. The data structure allows for easy compression, storage, segmentation, and reconstruction of volumetric data obtained from scanning a mammalian brain at submicron resolution, using threedimensional light microscopy (knifeedge scanning microscopy (KESM), confocal microscopy (CFM), and multiphoton microscopy (MPM)). A hybrid technique using the polymerization algorithm and an existing vectorbased tracing algorithm is developed. Both the polymerized and the hybrid algorithm have been tested and their analyzed results are presented. |
| Publisher: | Texas A&M University |
| Subject: |
Segmentation Strategies
Visualization |
| URI: | http://hdl.handle.net/1969.1/3077 |
| Date: | 2004-12 |
Citation
(2004).
Segmentation strategies for polymerized volume data sets.
Master's thesis,
Texas A&M University.
Texas A&M University. Available electronically from
http : / /hdl .handle .net /1969 .1 /3077.
Files in this item
| Files | Size | Format | View |
|---|---|---|---|
| etd-tamu-2004C-CPSC-Doddapa.pdf | 9.674Mb |
View/ |
This item appears in the following Collection(s)
-
Electronic Theses, Dissertations, and Records of Study (2002-present) [10425]
Electronic Theses, Dissertations, and Records of Study Collection
Browse
