# title
Lossless compression of 3D MRI and CT data

# abstract
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 filters, 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 filters. We describe these filters with the help of a small filter description language, which is compiled into a shared object file and dynamically loaded at run time. The source code of the program is freely available for testing purposes.

# publicationOutlet
WAVELET APPLICATIONS IN SIGNAL AND IMAGE PROCESSING VI

# nameOfConference
Wavelet Applications in Signal and Imaging Processing VI

# publisher.label
SPIE, the international society for optics and photonics

# authorList[]
Klappenecker, A., May, F. U., & Beth, T.

# editorList[]
Laine, A. F., Unser, M. A., & Aldroubi, A.