Three-dimensional medical image compression using a wavelet transform with parallel computing

We have developed a 3D wavelet compression algorithm for medical images that achieves a good reconstruction quality at high compression ratios. The algorithm applies a 3D wavelet transformation to a volume image set, followed by a scalar quantization and entropy coding to the wavelet coefficients. We also implemented a parallel version of the 3D compression algorithm in a local area network environment. Multiple processors on different workstations on the network are utilized to speed up the compression or decompression process. The 3D wavelet transform has been applied to 3D MR volume images and the results are compared with the results obtained using a 2D wavelet compression. Compression ratios achieved with the 3D algorithm are 40 - 90% higher than that of using the 2D compression algorithm. The results of applying parallel computing to the 3D compression algorithm indicate that the efficiency of the parallel algorithm ranges from 80 - 90%.