Purpose: Mammographic density is a strong risk factor for breast cancer. However, whether changes in mammographic density due to HRT are associated with risk remains unclear. The aim of this study is to provide a framework for accurate interval change analysis in temporal pairs of mammograms of patients undergoing HRT treatment using consistent and fully automatic registration framework.

Methods: The combination of B-spline based registration and consistent image registration is proposed that simplify the search for optimal deformation and does not require speci¿cation of landmarks. Kullback-Lieber  distance is used as a similarity metric which makes this method more robust against di¿erent image resolutions and other intensity based artifacts during temporal scan of mammograms.

Results: Registration was performed on the pairs of mammograms from longitudinal double blind placebo controlled HRT study that includes 39 placebo and 36 HRT treated volunteers for two years. The method’s performance was evaluated by an experienced radiologist.Validation study showed that method has given an optimal consistency error of 36 pixels(mm) with average computation time 45s.

Conclusions:  The work describes a novel approach for consistent and robust registartion framework for interval change analysis in pairs of mammograms. This would lead radiologist to asses the risk of individual patient by examining the changes in tissue structure and density due to harmonal replacement therapy.