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Proceedings Paper

Analysis of compression of 4D volumetric medical image datasets using multi-view (MVC) video coding methods
Author(s): Uwe-Erik Martin; André Kaup
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Paper Abstract

Due to the huge amount of data and the increasing usage, compression of 4D medical data sets is essential. These datasets consist of a number of sampled volume elements varying in time and are compressed either with spatial transformation based (e.g. JPEG2000-3D) or motion estimation based schemes. This paper presents a combined approach incorporating both, temporal and spatial information at the same time to compress 4D medical datasets. It is adopting a very similar four-dimensional Multi-View-Coding (MVC) scheme which is known from video processing to 4D medical datasets and compares experimental results with H.264 compression. Rate distortion characteristics show the advantages of such a combined spatio-temporal approach.

Paper Details

Date Published: 3 September 2008
PDF: 8 pages
Proc. SPIE 7075, Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications XI, 707507 (3 September 2008); doi: 10.1117/12.794483
Show Author Affiliations
Uwe-Erik Martin, Siemens AG (Germany)
André Kaup, Univ. of Erlangen-Nuremberg (Germany)


Published in SPIE Proceedings Vol. 7075:
Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications XI
Mark S. Schmalz; Gerhard X. Ritter; Junior Barrera; Jaakko T. Astola, Editor(s)

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