IMAGE SEGMENTATION

Segmentation of breast tumors in mammograms using fuzzy sets

[+] Author Affiliations
Denise Guliato

Federal University of Uberla?ndia, Department of Informatics, Laborato´rio de Bioinforma´tica, Campus Santa Mo?nica, Av. Joa˜o Naves de A´vila, 2160, 38400-089?Uberla?ndia, MG, Brazil E-mail: guliato@ufu.br

Rangaraj M. Rangayyan

University of Calgary, Departments of Electrical and Computer Engineering and Radiology, 2500 University Dr NW, Calgary, Alberta?T2N?1N4, Canada E-mail: ranga@enel.ucalgary.ca

Walter A. Carnielli

Universidade de Campinas, Centro de Lo´gica e Epistemologia, CP 6133, 13081-970?Campinas, SP, Brazil

Joa˜o A. Zuffo

Escola Polite´cnica da Universidade de Sa˜o Paulo, Laborato´rio de Sistemas Integra´veis, Divisa˜o de Sistemas Digitais, Av. Prof. Luciano Gualberto, tr. 3-158, 05508-900?Sa˜o Paulo, SP, Brazil

J. E. Leo Desautels

Screen Test Alberta, 120, 1040 7th Avenue SW, Calgary, Alberta?T2P?3G9, Canada ?

J. Electron. Imaging. 12(3), 369-378 (Jul 01, 2003). doi:10.1117/1.1579017
History: Received Sep. 6, 2000; Revised Dec. 19, 2001; Revised Nov. 5, 2002; Revised Jan. 24, 2003; Accepted Mar. 4, 2003; Online July 23, 2003
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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 SPIE and IS&T.

© 2003 SPIE and IS&T

Citation

Denise Guliato ; Rangaraj M. Rangayyan ; Walter A. Carnielli ; Joa˜o A. Zuffo and J. E. Leo Desautels
"Segmentation of breast tumors in mammograms using fuzzy sets", J. Electron. Imaging. 12(3), 369-378 (Jul 01, 2003). ; http://dx.doi.org/10.1117/1.1579017


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