MAMMOGRAPHIC DENSITY ESTIMATION AND CLASSIFICATION USING SEGMENTATION AND PROGRESSIVE ELIMINATION METHOD
Indra Kanta Maitra, Sanjay Nag, Samir Kumar Bandyopadhyay · International Journal of Image and Graphics · 2013
For establishing risk factor of breast cancer requires highly specific breast density measure that can result in a more focused breast cancer prevention, diagnosis and treatment. This paper proposes a new CAD system for density estimation using progressive elimination method. The lower intensity pixels are eliminated in multiple phases by targeting specific intensity bands in each phase, using established statistical techniques. Local Standard Deviation (LSD) values are used to identify significant transitions and MLSD values to isolate the most significant transitions or edges. The results are compared to ACR BI RAD system of classification to establish the risk factor. Accuracy estimation on the proposed segmentation method signifies satisfactory qualitative results. The proposed algorithm implemented on all 322 mammograms of MIAS shows 73.91% agreement. The obtained Kappa (κ) value for the proposed method is 0.673.