Fuzzy PGA filter technique performance on the mini-MIAS database of mammograms. (2015)

• Record Type: Journal Article
• Authors: Parcero, Estibaliz; Segrelles, Damian; Vidal, Vicente; Verdu, Gumersindo
• Is Part Of: International journal of image mining. Volume 1:Number 2/3(2015)
• Page Start: 189
• Page End: 207
• Publication Date: 2015
• Subjects: medical images -- peer group average -- fuzzy PGA filter -- mammograms -- mini-MIAS -- radiation dose -- grid infrastructure -- mammography -- image processing -- peak SNR -- signal-to-noise ratio -- breast tissue -- breast screening; Image processing -- Periodicals; Data mining -- Periodicals; 006.42
• Languages: English
• ISSNs: 2055-6039

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.