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

被引:2
|
作者
Zhang, Yan [1 ]
Passmore, Peter J. [2 ]
Bayford, Richard H. [3 ]
机构
[1] Univ Hull, Dept Comp Sci, Kingston Upon Hull HU6 7RX, N Humberside, England
[2] Middlesex Univ, Sch Engn & Informat Sci, London NW4 4BT, England
[3] Middlesex Univ, Sch Hlth & Social Sci, Dept Nat Sci, London NW4 4BT, England
关键词
visualization; multidimensional image; multimodal image; task-based visualization; Cubic Task Explorer; electrical impedance tomography; ELECTRICAL-IMPEDANCE TOMOGRAPHY; REGIONAL LUNG VENTILATION; EIT; PRESSURE; GRAVITY; IMAGES; TIME;
D O I
10.1098/rsta.2009.0084
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页码:3121 / 3148
页数:28
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