In this paper, a three-dimensional (3-D) compression method based on separable wavelet transform is discussed in detail.The most commonly used digital modalities generate multiple slices in a single examination, which are normally anatomically or physiologically correlated to each other. 3-D wavelet compression methods can achieve more efficient compression by exploring the correlation between slices. The first step is based on a separable 3-D wavelet transform. Considering the difference between pixel distances within a slice and those between slices, one biorthogonal Antoninin filter bank is applied within two-dimensional slices and a second biorthogonal Villa4 filter bank on the slice direction. Then, s+P transform is applied in the low-resolution wavelet components and an optimal quantizer is presented after analysis of the quantization noise. We use an optimal bit allocation algorithm, which, instead of eliminating the coefficients of highresolution components in smooth areas, minimizes the system reconstruction distortion at a given bit-rate. Finally, to remain high coding efficiency and adapt to different properties of each component, a comprehensive entropy coding method is proposed, in which arithmetic coding method is applied in high-resolution components and adaptive Huffman coding method in low-resolution components. Our experimental results are evaluated by several image measures and our 3-D wavelet compression scheme is proved to be more efficient than 2-D wavelet compression.