부산대학교 도서관

Current breast cancer risk prognosis methods have high prognostic variability which affects the chemotherapy decisions. Image analysis is a structure analysis tool that aids existing risk prognosis methods in order to improve quality of the prognosis. Fractal image analysis has been rarely used on breast tumor histology images for prognostic purposes and this paper deals with one such study using monofractal and multifractal analysis. Invasive breast tumor histology samples were used based on the absence of any systemic treatment. Obtained images were divided into two groups, named high and low risk, based on the risk prognosis for survival. Images were further subjected to computational analysis using binary and outline fractal dimensions, lacunarity for monofratal analysis and generalized dimension for multifractal analysis. Binary and outline fractal dimensions, as well as generalized dimension yielded statistically significant distinction between high risk and low risk groups. Lacunarity was also different but not statistically significant.