1 July 2003 Segmentation of breast tumors in mammograms using fuzzy sets
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Defining criteria to determine precisely the boundaries of masses in mammograms is a difficult task. The problem is compounded by the fact that most malignant tumors possess fuzzy boundaries with a slow and extended transition from a dense core region to the surrounding less-dense tissues. We propose two segmentation methods that incorporate fuzzy concepts. The first method determines the boundary of a mass or tumor by region growing after a preprocessing step based on fuzzy sets to enhance the region of interest (ROI). Contours provided by the method have demonstrated a good match with the contours drawn by a radiologist, as indicated by good agreement between the two sets of contours for 47 mammograms. The second segmentation method is a fuzzy region-growing method that takes into account the uncertainty present around the boundaries of tumors. The difficult step of deciding on a crisp boundary is obviated in the proposed method. Mea-sures of inhomogeneity computed from the pixels present in a suitably defined fuzzy ribbon have indicated potential use in classifying the masses and tumors as benign or malignant, with a sensitivity of 0.8 and a specificity of 0.9.
© (2003) Society of Photo-Optical Instrumentation Engineers (SPIE)
Denise Guliato, Denise Guliato, Rangaraj M. Rangayyan, Rangaraj M. Rangayyan, Walter A. Carnielli, Walter A. Carnielli, Joao Antonio Zuffo, Joao Antonio Zuffo, J. E. Leo Desautels, J. E. Leo Desautels, } "Segmentation of breast tumors in mammograms using fuzzy sets," Journal of Electronic Imaging 12(3), (1 July 2003). https://doi.org/10.1117/1.1579017 . Submission:

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