document: Lossy to lossless object-based coding of 3-D MRI data We propose a fully three-dimensional -LRB- 3-D -RRB- object-based coding system exploiting the diagnostic relevance of the different regions of the volumetric data for rate allocation . The data are first decorrelated via a 3-D discrete wavelet transform . The implementation via the lifting steps scheme allows to map integer-to-integer values , enabling lossless coding , and facilitates the definition of the object-based inverse transform . The coding process assigns disjoint segments of the bitstream to the different objects , which can be independently accessed and reconstructed at any up-to-lossless quality . Two fully 3-D coding strategies are considered : embedded zerotree coding -LRB- EZW-3D -RRB- and multidimensional layered zero coding -LRB- MLZC -RRB- , both generalized for region of interest -LRB- ROI -RRB- - based processing . In order to avoid artifacts along region boundaries , some extra coefficients must be encoded for each object . This gives rise to an overheading of the bitstream with respect to the case where the volume is encoded as a whole . The amount of such extra information depends on both the filter length and the decomposition depth . The system is characterized on a set of head magnetic resonance images . Results show that MLZC and EZW-3D have competitive performances . In particular , the best MLZC mode outperforms the others state-of-the-art techniques on one of the datasets for which results are available in the literature
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