Abstract
The final diagnosis in coronary angiography has to be performed on the original images, therefore the lossless compression schemes play a key role in medical data base management and tele-diagnosis applications. This work proposes a wavelet based compression scheme that is able to operate in the lossless mode. The quantization module implements a new modality for the coding of the coefficient's significance map that is more effective than the classical zero-tree representation. The experimental results obtained on a set of 20 angiograms show that the algorithm outperforms with 0.38 bpp the embedded zero-tree coder combined with the lifting scheme, with 0.20 bpp the set partitioning coder and with 0.70 bpp the lossless JPEG. The scheme is a good candidate in applications like remote browsing through large image data sets and real-time archiving of coronary angiograms.
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