Lossless Compression of 3D MRI and CT Data

We propose a conceptually simple method for lossless compression of medical image and volume data. The method can be divided into three steps: the input data is decomposed into several subbands with the help of nonlinear lifting lters, the resulting subbands are block-sorted according to a method suggested by Burrows and Wheeler, and the redundancy is removed with the help of an adaptive arithmetic coder. Moreover, we suggest a new method to implement (non-linear) lifting lters. We describe these lters with the help of a small lter description language, which is compiled into a shared object le and dynamically loaded at run time. The source code of the program is freely available for testing purposes.