SOFT COMPUTING BASED DECISION MAKING APPROACH FOR TUMOR MASS IDENTIFICATION IN MAMMOGRAM
Mahua Bhattacharya, Arpita Das · International Journal of Bioinformatics Research · 2009
An intelligent computer aided diagnosis system can be very helpful for radiologist in detecting and diagnosing breast cancer faster than typical screening program.This study attempted to segment the masses accurately and distinguish malignant from benign masses.The suspicious location of the breast masses are specified by the radiologists and then masses are accurately segmented using fuzzy c-means clustering technique.Fourier descriptors are utilized for the extraction of shape features of mammographic masses.These shape features along with the texture features are fed to the input of the ANFIS classifier for determination of the masses as benign, lobular or malignant.The classification system utilizes a simple Euclidian distance metric to determine the degree of malignancy.The study involves 40 digitized mammograms from MIAS, BIRADS database and has to be found 87% correct classification rate.