Logo der Universität Wien

Visualization and exploration of time-varying medical image data sets

Abstract

In this work, we propose and compare several methods for the vi- sualization and exploration of time-varying volumetric medical im- ages 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 syn- thetic 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.

Grafik Top
Authors
Grafik Top
Supplemental Material
Citation
Category
Paper in Conference Proceedings or in Workshop Proceedings (Full Paper in Proceedings)
Event Title
Graphics Interface 2007
Divisions
Visualization and Data Analysis
Subjects
Computergraphik
Event Location
Montreal
Event Type
Conference
Event Dates
28 - 30 May 2007
Date
May 2007
Export
Grafik Top
Contact us
Faculty of Computer Science
University of Vienna

Währinger Straße 29
A-1090 Vienna