In this paper, new mass features based on inter-view similarity in DBT projection views are proposed for classifying masses, aiming to effectively reducing false-positives (FPs). The proposed features are focused on utilizing inter-view information in projection views. The FPs induced by overlapping tissues of different depth could be observed differently between projection views, while masses could appear similar. To utilize the observation, the inter-view similarity measure is developed by utilizing the normalized cross-correlation between ROIs in projection views. In the analysis of inter-view similarities of masses and FPs, it is showed that inter-view similarities of FPs are lower than those of masses. To that end, new features are proposed to encode aforementioned difference of inter-view similarities between FPs and masses. Experimental results show that the proposed features can improve the mass classification performance in projection views in terms of the area under the ROC curve.

Date Published: 20 March 2015
PDF: 6 pages
Proc. SPIE 9414, Medical Imaging 2015: Computer-Aided Diagnosis, 941425 (20 March 2015);

Published in SPIE Proceedings Vol. 9414:
Medical Imaging 2015: Computer-Aided Diagnosis
Lubomir M. Hadjiiski; Georgia D. Tourassi, Editor(s)