Display of Surfaces from Volume Data
IEEE Computer Graphics and Applications
VIS '97 Proceedings of the 8th conference on Visualization '97
Isosurface extraction in time-varying fields using a temporal branch-on-need tree (T-BON)
VIS '99 Proceedings of the conference on Visualization '99: celebrating ten years
A fast volume rendering algorithm for time-varying fields using a time-space partitioning (TSP) tree
VIS '99 Proceedings of the conference on Visualization '99: celebrating ten years
Very high resolution simulation of compressible turbulence on the IBM-SP system
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Fast detection of meaningful isosurfaces for volume data visualization
Proceedings of the conference on Visualization '01
4D space-time techniques: a medical imaging case study
Proceedings of the conference on Visualization '01
Space and Time Shape Constrained Deformable Surfaces for 4D Medical Image Segmentation
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
Interactive feature specification for focus+context visualization of complex simulation data
VISSYM '03 Proceedings of the symposium on Data visualisation 2003
Case Study: Visualizing Sets of Evolutionary Trees
INFOVIS '02 Proceedings of the IEEE Symposium on Information Visualization (InfoVis'02)
A Hybrid Layout Algorithm for Sub-Quadratic Multidimensional Scaling
INFOVIS '02 Proceedings of the IEEE Symposium on Information Visualization (InfoVis'02)
Steerable, Progressive Multidimensional Scaling
INFOVIS '04 Proceedings of the IEEE Symposium on Information Visualization
4D shape priors for a level set segmentation of the left myocardium in SPECT sequences
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Integrated four dimensional registration and segmentation of dynamic renal MR images
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
Case study: visual analysis of complex, time-dependent simulation results of a diesel exhaust system
VISSYM'04 Proceedings of the Sixth Joint Eurographics - IEEE TCVG conference on Visualization
Simultaneous classification of time-varying volume data based on the time histogram
EUROVIS'06 Proceedings of the Eighth Joint Eurographics / IEEE VGTC conference on Visualization
Visualization of time-varying volumetric data using differential time-histogram table
VG'05 Proceedings of the Fourth Eurographics / IEEE VGTC conference on Volume Graphics
Generating time lines with virtual words for time-varying data visualization
Proceedings of the 5th International Symposium on Visual Information Communication and Interaction
Interactive visualization of function fields by range-space segmentation
EuroVis'09 Proceedings of the 11th Eurographics / IEEE - VGTC conference on Visualization
Semi-automatic time-series transfer functions via temporal clustering and sequencing
EuroVis'09 Proceedings of the 11th Eurographics / IEEE - VGTC conference on Visualization
Visual exploration of time-series data with shape space projections
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
Visualization and analysis of 3D time-varying simulations with time lines
Journal of Visual Languages and Computing
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In this work, we propose and compare several methods for the visualization and exploration of time-varying volumetric medical images based on the temporal characteristics of the data. The principle idea is to consider a time-varying data set as a 3D array where each voxel contains a time-activity curve (TAC). We define and appraise three different TAC similarity measures. Based on these measures we introduce three methods to analyze and visualize time-varying data. The first method relates the whole data set to one template TAC and creates a 1D histogram. The second method extends the 1D histogram into a 2D histogram by taking the Euclidean distance between voxels into account. The third method does not rely on a template TAC but rather creates a 2D scatter-plot of all TAC data points via multi-dimensional scaling. These methods allow the user to specify transfer functions on the 1D and 2D histograms and on the scatter plot, respectively. We validate these methods on synthetic dynamic SPECT and PET data sets and a dynamic planar Gamma camera image of a patient. These techniques are designed to offer researchers and health care professionals a new tool to study the time-varying medical imaging data sets.