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6 April 1995 Wavelet transform for local tomography reconstruction
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Abstract
We propose a new experimental data acquisition method which acquires multiple exposures through a windowed x-ray radiation profile. The tapered profile is localized at the target region with a reduced radiation dosage but must be repeated at a few discrete shifts outside the target region to cover the whole slice. Such an approximated spatial window-convolution projection, a weighted-shifted radon transform, is ideally suited for the wavelet transform (WT) which is a bank of constant-Q matched filters creating a local space-scale joint representation. It is more efficient than the Fourier transform (FT) for any local signal analysis. It requires fewer basis terms and provides better signal-to-noise ratio enhancement than FT. Thus, the WT version of the central slice theorem (CST) yields an image reconstruction method. Because of the compact support and the design flexibility of the wavelet bases, this new approach has the potential of requiring fewer of the weighted x-ray projections, in which a lower radiation dosage is used, than standard tomography. Despite the sparser data set, a reconstructed image of similar quality to that created by standard FT tomography can be achieved. Moreover, the WT using the tapered radiation cuts can provide a multi-resolution feature extraction for use in artificial neural network-based automatic pattern classification.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Harold H. Szu, Joseph T. DeWitte Jr., Joseph P. Garcia, Brian A. Telfer, Tim E. Olson, Dennis M. Healy Jr., and Rui J. P. de Figueiredo "Wavelet transform for local tomography reconstruction", Proc. SPIE 2491, Wavelet Applications II, (6 April 1995); https://doi.org/10.1117/12.205442
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