Fast Detection of Mammographic Masses with Difficult Case Exclusion

Breast cancer is one of the most common forms of cancer among women. Currently mammography is the most efficient method for early detection. A simple mammographic mass detection system and two different methods for difficult case exclusion are presented in this paper. The mass detection system uses a modified version of the AFUM mass detection algorithm. The first difficult case filtering method is based on tissue density estimation, the second one on mass candidate count. The system was tested on 600 mammographic cases, each containing 4 images. Case-level performance was measured in malignant mass detection first without and then with difficult case exclusion.