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Proceedings Paper

Lossless compression of 3D MRI and CT data
Author(s): Andreas Klappenecker; Frank U. May; Thomas Beth
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Paper 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.

Paper Details

Date Published: 19 October 1998
PDF: 10 pages
Proc. SPIE 3458, Wavelet Applications in Signal and Imaging Processing VI, (19 October 1998); doi: 10.1117/12.328131
Show Author Affiliations
Andreas Klappenecker, Univ. of Karlsruhe (United States)
Frank U. May, Univ. of Karlsruhe (Germany)
Thomas Beth, Univ. of Karlsruhe (Germany)

Published in SPIE Proceedings Vol. 3458:
Wavelet Applications in Signal and Imaging Processing VI
Andrew F. Laine; Michael A. Unser; Akram Aldroubi, Editor(s)

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