Multiple-level Logarithmic Wavelets for Mammographic Contrast Enhancement: A Statistical Analysis for Wavelet Selection

Authors

  • Damian Valdés Santiago University of Havana
  • Daniel Mesejo León Pontifitial University of Rio de Janeiro
  • Ángela León Mecías University of Havana

DOI:

https://doi.org/10.13053/cys-22-2-2555

Keywords:

Mammograms, contrast enhancement, Discrete Wavelet Transform, Symmetric Logarithmic Image Processing model, Logarithmic Discrete Wavelet Transform

Abstract

Low doses radiation in mammography results in low contrast images. In this paper we propose a method to enhance the contrast in mammography; it combines the modification of the coefficients of the Logarithmic Discrete Wavelet Transform using the Local Correlation method and Symmetric Logarithmic Image Processing model. Experimental results shown the better performance for the anomalies known as calcifications and masses. This paper also presents a methodology to select a combination of decomposition levels to be processed for good contrast improvement according to the values of measures based on region of interest. This procedure relies on Principal Components Analysis of the data. The experiments show that the chosen combination of levels can improve the contrast in mammograms, and that the regions of interest definition is an important factor to explain the poor contrast improvement of some anomalies.

Author Biographies

Damian Valdés Santiago, University of Havana

Department of Applied Mathematics

Ángela León Mecías, University of Havana

Department of Applied Mathematics

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Published

2018-06-30

Issue

Vol. 22 No. 2 (2018): Thematic Issue on Numerical and Evolutionary Optimization (Guest editors: L. Trujillo, Y. Maldonado, O. Schuetze)

Section

Articles

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