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Quantifying image quality at breast periphery vs mammary gland in mammography using wavelet analysis

L Costaridou, PhD, P Sakellaropoulos, MSc, A P Stefanoyiannis, MSc, E Ungureanu, MSc and G Panayiotakis, PhD

Department of Medical Physics, School of Medicine, University of Patras, 26500 Patras, Greece



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Figure 1. Example of local contrast visualization at the first four scales of gradient magnitude images of the non-subsampled biorthogonal discrete wavelet transform. 1.a and 2.a show original uniform and low contrast detail regions of interest, respectively. 1.b–1.e and 2.b–2.e show corresponding gradient magnitude images.

 


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Figure 2. Sampling mammary gland and breast periphery regions in a craniocaudal mammogram. (a) Positioning of regions of interest (ROIs). (b) Example of ROI positioning and size selection, facilitated by gradient magnitude images.

 


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Figure 3. (a,b) Assessment of adequate number of sampling regions of interest (ROIs) for contrast indicator of mammary gland and breast periphery regions, corresponding to the second scale. (c,d) Assessment of adequate number of sampling ROIs for noise indicator of mammary gland and breast periphery regions, corresponding to the first scale. Arrows indicate the adequate number of ROIs.

 


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Figure 4. Instances of the medical image visualization tool used. (a) The original region of interest (ROI) is positioned at the mammary gland, while the reference ROI for noise estimation is positioned at the background of the mammogram. (b) Gradient magnitude images corresponding to the first two scales of the original and reference ROI. (c,d) Histogram plots and statistical information for the gradient magnitude images including the contrast indicator (ROI mean value) at the second scale (c) and the noise indicator (ROI noise level) measured at the first scale (d).

 


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Figure 5. Relationship of (a) proposed contrast indicator to nominal contrast and (b) proposed noise indicators to amount of noise expressed as standard deviation {sigma} of a Gaussian noise distribution . Standard deviation values are normalized to the maximum pixel value for 12 bit pixel depth. {blacklozenge}, scale 1; {blacksquare}, scale 2; {blacktriangleup}, scale 3; x , scale 4.

 





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