Testing a wavelet based noise reduction method using computer-simulated mammograms

Abstract

A wavelet based method of noise reduction has been tested for mammography using computer-simulated images for which the truth is known exactly. This method is based on comparing two images at different scales, using a crosscorrelation-function as a measure of similarity to define the image modifications in the wavelet domain. The computersimulated images were calculated for noise-free primary radiation using a quasi-realistic voxel phantom. Two images corresponding to slightly different geometry were produced. Gaussian noise was added with a mean value of zero and a standard deviation equal to 0.25% to 10% of the actual pixel value to simulate quantum noise with a certain level. The added noise could be reduced by more than 70% using the proposed method without any noticeable corruption of the structures for 4% added noise. The results indicate that it is possible to save 50% dose in mammography by producing two images (each 25% of the dose for a standard mammogram). Additionally, a reduction or even a removal of the anatomical noise might be possible and therefore better detection rates of breast cancer in mammography might be achievable.

Comparison of breast ductal branching pattern classification using x-ray galactograms and MR autogalactograms

“…Such synthetic images have been used in analysis of parenchymal pattern 5 , tissue specific dosimetry in mammography 6,7 , evaluation of mammogram registration methods 8 , and evaluation of wavelet-based mammogram processing techniques 9 .…”