Morphological texture-based classification of abnormalities in mammograms
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abstract
This paper presents a computer-based classification scheme for masses in mammograms. The developed scheme is based on an introduced measure of surface fluctuation that captures texture roughness associated with the surface of an abnormality mass area. First local maxima/minima along rows and columns of a marked abnormality area in a mammogram are located. Morphological erosion is then applied to these maxima/minima to obtain the degree of surface roughness or coarseness within this area. The erosion is done for many sizes of a structuring element. This process is similar to the texture `feeling' one gets by moving a finger horizontally and vertically on a surface. The developed scheme was tested on 108 mammograms with pathologically proven results; 55 benign and 53 malignant masses. All mammograms were digitized at 50-micron resolution. The Receiver Operating Characteristic (ROC) curves for different sizes of a structuring element were plotted. The average area underneath these curves was obtained to be 0.92. The corresponding clinical evaluation by the radiologist gave an area of 0.86. The results obtained indicate the potential of using this classification scheme as an electronic second opinion to lower the number of unnecessary biopsies.
