Task based visualization of 5D brain EIT data

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Task based visualization of 5D brain EIT data

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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

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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.

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