This work introduces a combination of image processing and analysis
methods that perform feature extraction, shape analysis and tomographic reconstruction of Electron Microscopy images. These have been implemented on
images of the AIDS virus interacting with neutralizing molecules. The AIDS
virus spike is the primary target of drug design as it is directly involved in
infecting host cells. First, a fully automated technique is introduced that can
extract sub-volumes of the AIDS virus spike and be used to build a statistical
model without the need for any user supervision. Such an automatic feature
extraction method can significantly enhance the overall process of shape analysis
of the AIDS virus spike imaged through the electron microscope. Accurate
models of the virus spike will help in the development of better drug design
strategies.
Secondly, a tomographic reconstruction method implemented using a
shape based regularization technique is introduced. Spatial models of known
features in the structure being reconstructed are integrated into the reconstruction
process as regularizers. This regularization scheme is driven locally
through shape information obtained from segmentation and compared with a
known spatial model. This method shows reduced blurring, and an improvement
in the resolution of the reconstructed volume was also measured. It performs better than popular current techniques and can be extended to other tomographic modalities. Improved Electron Tomography reconstructions will provide better structure elucidation and improved feature visualization, which can aid in solving key biological issues. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/ETD-UT-2012-05-4972 |
| Date | 11 July 2012 |
| Creators | Gopinath, Ajay, 1980- |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Type | thesis |
| Format | application/pdf |
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