Lossy-to-lossless compression of medical volumetric data using three-dimensional integer wavelet transforms

We study lossy-to-lossless compression of medical volumetric data using three-dimensional (3-D) integer wavelet transforms. To achieve good lossy coding performance, it is important to have transforms that are unitary. In addition to the lifting approach, we first introduce a general 3-D integer wavelet packet transform structure that allows implicit bit shifting of wavelet coefficients to approximate a 3-D unitary transformation. We then focus on context modeling for efficient arithmetic coding of wavelet coefficients. Two state-of-the-art 3-D wavelet video coding techniques, namely, 3-D set partitioning in hierarchical trees (Kim et al, 2000) and 3-D embedded subband coding with optimal truncation (Xu et al, 2001), are modified and applied to compression of medical volumetric data, achieving the best performance published so far in the literature--both in terms of lossy and lossless compression. Index Terms--3-D ESCOT, 3-D SPIHT, bit shifting, context modeling, lossy-to-lossless compression, medical volumetric data.