Title :
Segmentation of breast tumors in mammograms by fuzzy region growing
Author :
Guliato, Denise ; Rangayyan, Rangaraj M. ; Carnielli, Walter A. ; Zuffo, JoÃo A. ; Desautels, J. E Leo
Author_Institution :
Dept. of Inf., Univ. Fed. de Uberlandia, Brazil
fDate :
29 Oct-1 Nov 1998
Abstract :
Segmentation of tumor regions in mammograms is not easy due to the low contrast and the fuzzy nature of the boundaries of malignant tumors. General image segmentation procedures do not consider the uncertainty present around the boundaries of a tumor region. In this paper we present a segmentation method based on fuzzy region growing. The procedure starts with a seed pixel, and uses a fuzzy membership function based upon statistical measures of the region being grown. Results of testing with several mammograms indicate that the method can provide boundaries of tumors close to those drawn by an expert radiologist. The regions obtained preserve the transition information present around tumor boundaries. Statistical measures computed from the resulting regions have shown the potential to classify masses and tumors as benign or malignant
Keywords :
fuzzy set theory; image segmentation; mammography; medical image processing; tumours; boundaries of malignant tumors; fuzzy membership function; fuzzy region growing; fuzzy sets; image segmentation; low contrast; mammograms; seed pixel; segmentation of breast tumors; statistical measures; Breast cancer; Breast neoplasms; Breast tumors; Clustering algorithms; Image segmentation; Iterative algorithms; Low earth orbit satellites; Malignant tumors; Particle measurements; Pixel;
Conference_Titel :
Engineering in Medicine and Biology Society, 1998. Proceedings of the 20th Annual International Conference of the IEEE
Conference_Location :
Hong Kong
Print_ISBN :
0-7803-5164-9
DOI :
10.1109/IEMBS.1998.745618