Fuzzy PGA filter technique performance on the mini-MIAS database of mammograms Online publication date: Thu, 12-Nov-2015
by Estibaliz Parcero; Damian Segrelles; Vicente Vidal; Gumersindo Verdu
International Journal of Image Mining (IJIM), Vol. 1, No. 2/3, 2015
Abstract: Medical image processing promises major advances in medicine as higher fidelity images are produced, e.g., filters improve image quality to facilitate diagnosis or reduce radiation absorption. We evaluated the fuzzy peer group averaging technique in terms of effectiveness and stability. Effectiveness was measured by applying the filter to a set of mammograms and comparing the results to the obtained by different methods. This technique obtained the best peak signal-to-noise ratio values. Stability means that a filter applied to a mammogram must perform adequately in any case regardless of the type of tissue, the class of abnormality, and the severity. Thus, this part of the study focused on validating the stability of the fuzzy peer group averaging technique for its use in mammograms by demonstrating its effectiveness regardless the case. The normal distribution of the peak signal-to-noise ratio in the frequency histograms obtained validated this assumption.
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