Visualization and exploration of time-varying medical image data sets

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 dynam...

• Type: Conference
• Year: 2007
• Where: GRAPHICSINTERFACE
• Authors: Zhe Fang, Torsten Möller, Ghassan Hamarneh, Anna Celler
• Keywords: 1D Histogram, Computer Graphics, Data Sets, GRAPHICSINTERFACE 2007, Time-varying Data