|Title:||Wavelet localization of tomography image reconstruction|
Hong Kong Polytechnic University -- Dissertations
|Pages:||78,  leaves : ill. ; 31 cm|
|Abstract:||The objective of the project is to study the techniques for reducing the radiation exposure in tomography image reconstruction as compared to the standard method. In these techniques, the wavelet transform is used to essentially localize the radiation projection process in tomographic imaging. This enables the projections to be concentrated on the interested area to reduce the radiation exposure required. In this dissertation, we will have a detailed description on the theories and simulations of these algorithms. The first part of the dissertation is mainly based on the research result in , where an algorithm was developed to interpolate the coarse wavelet coefficients from full projection to reduce the radiation exposure. We will exam this algorithm with comparison to a simple linear interpolation method. We will show by simulation and calculation that both methods give results with similar quality. Since the wavelet transform is also a good interpolation tool, we find that the missed data at reduced projection can be interpolated by using the wavelet transform. Moreover, the wavelet transform allows the possibility of multiresolution interpolation hence further reducing the radiation exposure. Base on the sampling scheme in  and the time-scale relationship properties of the wavelet transform, we develop a sampling scheme that the reduction of radiation exposure is doubled as compared to that in . We find that it not only maintains the quality of the reconstructed image in the interested area, but also the quality of the non-interested area of the image is improved. We believe that this technique represents a significant contribution towards this effort.|
|Rights:||All rights reserved|
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