A A fast and fully automatic registration approach for mammographic images
Mammogram registration is one of the important steps in breast cancer progression assessment. In this paper we present an automated approach for mammographic images registration which is an improved method based on a previously proposed approach by the authors. The proposed method will run on a sample of 27 mammograms from the Parto Teb Azma Imaging Center. In the first step of this method, initial misalignment between fixed image and moving images are removed by using pre-processing of Mammograms. Then, we extract corresponding point pairs with using Local curvature and image intensity features as parameters for the TPS transformation function. At last, a pair of mammograms is registered using Thin-Plate spline interpolation based on corresponding points on the two images. Performance of proposed method is measured by correlation coefficient (CC) and Sum of squared differences (SSD) criterions. We show that in addition to maximizing similarities and minimizing differences between two images, the second image retains its overall shape. The average of correlation coefficient of mammograms after image registration in the automated method increase to 0.3253 and the average of difference squared in the automated method will decrease to 0.1055.
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