Coronary artery calcification (CAC) as assessed with CT calcium score is the best biomarker for predicting future cardiac events. Dual energy (DE) chest radiography offers an inexpensive, low radiation-dose alternative to CT. We have shown CAC can be visualized using non-gated, 2-shot, DE chest x-ray imaging. However, calcium signal from the ribs, superimposed on the CAC signal, can interfere with both image registration and reader detection of CAC. To improve the registration algorithm and the detectability of CAC, we created an enhanced CAC visualization algorithm with automatic rib segmentation and suppression. In this paper, we trained an active appearance model to detect the spatial location of rib in the DE bone images. Then, we suppressed the rib signal in the single kVp images using a kernel-filter based method. After the rib suppression, we used affine and non-rigid registration to align the CAC in low and high kVp image. 1800 dual energy cases were used in our experiment after data augmentation on 60 cases. We evaluated the segmentation from the rib AAM using six-fold cross validation. The average dice coefficient of the rib segmentation in the heart region is 0.92. The reduction of CAC mis-registration by the enhanced CAC registration algorithm is evaluated using both simulated and clinical images. Adding rib suppression improves the image registration significantly. Our results show that in both simulated synthetic images and clinical images, the CAC overlap improves from 0% to > 50% after rib suppression. Results suggest that CAC visualization and registration can be significantly improved using the rib suppression when rib signal confounds CAC signal in DE chest radiography.