A Novel Breast Cancer Risk Assessment Scheme Design Using Dual View Mammograms

Abstract

Abstract. Computer aided diagnosis (CADx) schemes based on dual view mammograms are able to provide extra information compared to single view schemes. To explore an efficient and effective way for combining the information from different views, a new breast cancer risk analysis scheme was developed and tested in this study. 120 pairs of dual view mammograms from 120 women were used in this study. Three different groups of texture features and density features were extracted from both MLO view and CC view mammograms. The asymmetry score that measures the asymmetry levels of these two view mammograms was considered in our proposed scheme. 91 computational features on each view and 3 asymmetry measurements were computed and used for the proposed scheme. Three classifiers were used in our proposed scheme, one for each of the dual view mammograms, and the third one combined dual view scores with asymmetry measurements. The highest area under the curve (AUC) we obtained was 0.753 ± 0.039.