Coronary angiogram video compression using wavelet-based contourlet transform and region-of-interest technique

In this study, the authors have proposed a new rapid method for the compression of coronary angiogram video sequences. The method is based on the philosophy that diagnostically significant areas of the image should be allocated the greatest proportion of the total allocated bit-budget. The approach uses a wavelet-based contourlet transform coder based on the set partitioned embedded block coder. Incorporated into this framework is a region-of-interest (ROI) detection technique. The combined result is an approach that removes the low-level contourlet coefficients for some diagnostically insignificant regions of the image in an extremely efficient manner. This allows additional bits to be used within the ROI to improve the quality of the significant areas. The results are compared for a number of real data sets and evaluated by trained cardiologists.