Visualization of multidimensional and multimodal tomographic medical imaging data, a case study
Zhang, Yan, Passmore, Peter J. and Bayford, Richard (2009) Visualization of multidimensional and multimodal tomographic medical imaging data, a case study. Philosophical Transactions of the Royal Society of London. A: Mathematical and Physical Sciences, 367 (1900). pp. 3121-3148. ISSN 1364-503X
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Official URL: http://dx.doi.org/10.1098/rsta.2009.0084
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Multidimensional tomographic datasets contain physical properties defined over four-dimensional (e.g. spatial–temporal, spatial–spectral), five-dimensional (e.g. spatial–temporal–spectral) or even higher-dimensional domains. Multimodal tomographic datasets contain physical properties obtained with different imaging modalities. In medicine, four-dimensional data are widely used, five-dimensional data are emerging, and multimodal data are being used more often every day. Visualization is vital for medical diagnosis and surgical planning to interpret the information included in imaging data. Visualization of multidimensional and multimodal tomographic imaging data is still a challenging task. As a case study, our work focuses on the visualization of five-dimensional (spatial–temporal–spectral) brain electrical impedance tomography (EIT) data. In this paper, a task-based subset definition scheme is proposed: a task model named Cubic Task Explorer (CTE) is derived to support the visualization task exploration for medical imaging data, and a structured method for visualization system development called Task-based Multi-Dimensional Visualization (TMDV) is proposed. A prototype system named EIT5DVis is developed using the CTE model and TMDV method to visualize five-dimensional brain EIT data.
Online ISSN: 1471-2962
|Research Areas:||Science & Technology > Algorithms, Architecture & Networks|
Science & Technology > Biomedical Science
|Citations on ISI Web of Science:||1|
|Deposited On:||11 Jan 2010 05:39|
|Last Modified:||31 May 2013 15:40|
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