Visualization of multidimensional and multimodal tomographic medical imaging data, a case study

Zhang, Yan, Passmore, Peter J. ORCID logoORCID: https://orcid.org/0000-0002-5738-6800 and Bayford, Richard ORCID logoORCID: https://orcid.org/0000-0001-8863-6385 (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 [Article] (doi:10.1098/rsta.2009.0084)

Abstract

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.

Item Type: Article
Additional Information: Online ISSN: 1471-2962.
Theme Issue ‘New and emerging tomographic imaging’ compiled by Manuchehr Soleimani and Richard H. Bayford.
Research Areas: A. > School of Science and Technology > Computer Science
A. > School of Science and Technology > Computer Science > Artificial Intelligence group
A. > School of Science and Technology > Natural Sciences
A. > School of Science and Technology > Natural Sciences > Biophysics and Bioengineering group
ISI Impact: 1
Item ID: 3599
Useful Links:
Depositing User: Devika Mohan
Date Deposited: 11 Jan 2010 05:39
Last Modified: 11 Oct 2019 13:15
URI: https://eprints.mdx.ac.uk/id/eprint/3599

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