Paper
3 March 2012 Local spectral adaptive multitaper method with bilateral filtering for spectrum analysis of mammographic images
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Abstract
Estimation of the image power spectrum is fundamental to the development of a figure of merit for image performance analysis. We are investigating a new multitaper approach to determine power spectra, which provides a combination of low variance and high spectral resolution in the frequency range of interest. To further reduce the variance, the spectrum estimated by the proposed Local Spectral Adaptive Multitaper Method (LSAMTM) is subsequently smoothed in the frequency domain by bilateral filtering, while keeping the spectral resolution intact. This tool will be especially valuable in power spectrum estimation of images that deviate significantly from uniform white noise. The performance of this approach was evaluated in terms of spectral stability, variance reduction, bias and frequency precision. It was also compared to the conventional power spectrum method in several typical situations, including the noise power spectra (NPS) measurements of simulated projection images of a uniform phantom and NPS measurement of real detector images of a uniform phantom for two clinical digital mammography systems. Examination of variance reduction versus spectral resolution and bias indicates that the LSAMTM with bilateral filtering technique is superior to the conventional estimation methods in variance reduction, spectral resolution and in the prevention of spectrum leakage. It has the ability to keep both low variance and narrow spectral linewidth in the frequency range of interest. Up to 87% more variance reduction can be achieved with proper filtration and no sacrifice of frequency precision has been observed.
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Gang Wu, James G. Mainprize, and Martin J. Yaffe "Local spectral adaptive multitaper method with bilateral filtering for spectrum analysis of mammographic images", Proc. SPIE 8313, Medical Imaging 2012: Physics of Medical Imaging, 83134N (3 March 2012); https://doi.org/10.1117/12.911067
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KEYWORDS
Spectral resolution

Optical filters

Image filtering

Image analysis

Digital filtering

Spectrum analysis

Solids

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