Analysis of spatio-temporal prediction methods in 4D volumetric medical image datasets

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Martin UE, Kaup A
Publication year: 2008
Pages range: 525-528
ISBN: 978-1-4244-2570-9
ISSN: 1945-7871
Language: English


Abstract


Due to the huge amount of data and the increasing utilization of 4D medical image processing, compression of such data sets is essential. Unlike moving 3D objects in computer graphic applications, medical 4D datasets consist of a number of sampled volume elements, varying in time. Based on an analysis of H.264 compression for such data, this paper presents a spatio-temporal prediction scheme leveraging effective block-based prediction for 4D volumetric image data. Experimental results show that this new spatiotemporal approach achieves better prediction results than pure spatial or temporal schemes. © 2008 IEEE.


FAU Authors / FAU Editors

Kaup, André Prof. Dr.-Ing.
Lehrstuhl für Multimediakommunikation und Signalverarbeitung


External institutions
Siemens AG


How to cite

APA:
Martin, U.-E., & Kaup, A. (2008). Analysis of spatio-temporal prediction methods in 4D volumetric medical image datasets. In Proceedings of the 2008 IEEE International Conference on Multimedia and Expo, ICME 2008 (pp. 525-528). Hannover, DE.

MLA:
Martin, Uwe-Erik, and André Kaup. "Analysis of spatio-temporal prediction methods in 4D volumetric medical image datasets." Proceedings of the 2008 IEEE International Conference on Multimedia and Expo, ICME 2008, Hannover 2008. 525-528.

BibTeX: 

Last updated on 2019-10-05 at 17:38