Task based visualization of 5D brain EIT data

Subscribe (Full Service)


	Search: The ACM Digital Library The Guide

	Feedback
Take a look at the new version of this page: [ beta version ]. Tell us what you think.

Task based visualization of 5D brain EIT data

Full text

Pdf (533 KB)

Source

Symposium on Applied Computing archive
Proceedings of the 2009 ACM symposium on Applied Computing table of contents

Honolulu, Hawaii

SESSION: Computer application in health care track table of contents

Pages: 831-835

Year of Publication: 2009

ISBN:978-1-60558-166-8

Authors

Yan Zhang	University of Hull, Hull, UK
Peter J. Passmore	Middlesex University, London, UK
Richard H. Bayford	Middlesex University, London, UK

Sponsor

SIGAPP: ACM Special Interest Group on Applied Computing

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 8, Downloads (12 Months): 52, Citation Count: 0

Additional Information:

abstract references index terms collaborative colleagues

Tools and Actions:	Request Permissions Review this Article Save this Article to a Binder Display Formats: BibTeX EndNote ACM Ref

DOI Bookmark:	Use this link to bookmark this Article: http://doi.acm.org/10.1145/1529282.1529459 What is a DOI?

ABSTRACT

Visualization is vital for medical research and clinical applications to interpret information presented in medical imaging data. EIT (Electrical Impedance Tomography) is a recently developed medical imaging technique, which is able to collect 5D spectral-temporal-spatial data. Visualization of multi-dimensional medical imaging data is still a challenge. Making use of the TMDV (Task-based Multi-Dimensional Visualization) method and CTE (Cubic Task Explore) model, a task based prototype system, EIT5DVis, is developed for the visualization of 5D brain EIT data in this paper. The evaluation result demonstrates the usability of EIT5DVis prototype visualization system and the effectiveness of the TMVD method and CTE model for the visualization of multi-dimensional medical imaging data.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Bayford, R. H. (2006). "Bioimpedance Tomography (Electrical Impedance Tomography)", Review annuals. Vol 8: 63--91.
	2	Arnheim, R. (1997). Visual Thinking, University of California Press, Berkeley.
	3	Friston, K. J., C. D. Frith, et al. (1991). "Comparing functional (PET) images: the assessment of significant change." Journal of Cerebral Blood Flow Metabolism 11: 690--699.
	4	Yan Zhang , Peter J. Passmore , Rebecca J. Yerworth , Richard H. Bayford, Statistical Analysis for Brain EIT Images Using SPM, Proceedings of the Third International Conference on Medical Information Visualisation--BioMedical Visualisation, p.60-67, July 05-07, 2005 [doi>10.1109/MEDIVIS.2005.17]
	5	Yerworth R. J., Zhang Y., Tidswell T., Bayford R. H., and Holder D. S. (2007) "Use of statistical parametric mapping (SPM) to enhance electrical impedance tomography (EIT) image sets". Physiological Measurement, 28(7): S141-S152.
	6	Binnie, C., A. Rowan, et al. (1982). The 10--20 system. A Manual of Electroencephalographic Technology: 325--331.
	7	Tidswell, T., A. Gibson, et al. (2001). "Three-Dimensional Electrical Impedance Tomography of Human Brain Activity." NeuroImage 13(2): 283--294.