Benign and malignant breast tumors: Diagnosis using fractal measures

The work presents two measures of complexity, fractal dimension and lacunarity, in order to raise the precision in breast cancer diagnosis. A set of 40 cases of mammograms from patients corresponding to both benign (24 images) and malignant tumors (16 images) were analyzed. To improve the diagnostic process we proposed a method that combines the two fractal characteristics. For the processing of mammograms it was used two software programs, one for computing average fractal dimensions from the image contour, proposed by the authors, and the other (FracLac) to compute the average lacunarity on the binary image. In this way, classification rate increased from 90% (when using fractal dimension) to 100%. Finally, we proposed a framework for assisted diagnosis from the mentioned set of mammographic images.