Detection of breast cancer using independent component analysis

Screening mammograms remain the best method to protect women from breast cancer. To increase the value of this modality and reduce the strain on the radiologists; automation of detection is a necessity. In this paper we investigate combining principal component analysis (PCA) with independent component analysis (ICA) to identify regions of suspicious (ROS) from digitized mammographic films. The experimental results show that this combination has an accuracy of 79% in detecting abnormalities and 71.2% accuracy in the case of diagnosing the abnormality as benign or malignant.