A new method for the compression of angiogram video sequences is presented. 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 three-dimensional wavelet-coder based on the popular set partitioning in hierarchical trees algorithm. Incorporated into this framework are a region-of-interest (ROI) detection stage and a texture-modeling stage. The combined result is an approach that models the high-frequency wavelet coefficients for some diagnostically unimportant regions of the image in an extremely efficient manner. This allows additional bits to be used within the 1101 to improve the quality of the diagnostically significant areas. Results are compared far a number of real data sets and evaluated by trained cardiologists.
|Number of pages||11|
|Journal||IEEE Transactions on Information Technology in Biomedicine|
|Publication status||Published - 1 Jun 2004|