Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Real Time Volumetric Deformable Models for Surgery Simulation
VBC '96 Proceedings of the 4th International Conference on Visualization in Biomedical Computing
The visualization and measurement of left ventricular deformation
APBC '03 Proceedings of the First Asia-Pacific bioinformatics conference on Bioinformatics 2003 - Volume 19
The 3D visualization of brain anatomy from diffusion-weighted magnetic resonance imaging data
Proceedings of the 2nd international conference on Computer graphics and interactive techniques in Australasia and South East Asia
The visualization of myocardial strain for the improved analysis of cardiac mechanics
Proceedings of the 2nd international conference on Computer graphics and interactive techniques in Australasia and South East Asia
APVis '04 Proceedings of the 2004 Australasian symposium on Information Visualisation - Volume 35
Using a lightweight ontology of heart electrophysiology in an interactive web application
Companion Proceedings of the XIV Brazilian Symposium on Multimedia and the Web
GPU-accelerated direct volume rendering of finite element data sets
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
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Medical data sets now comprise a diverse range of measurements such as tissue densities, sensitivity to magnetization, blood flow velocity, and material strain. The size and complexity of medical data sets makes it increasingly difficult to understand, compare, analyze and communicate the data. Visualization is an attempt to simplify these tasks according to the motto "An image says more than a thousand words". Representing complex material properties, such as strain, as a single image improves the perception of features and pattern in the data, enables the recognition of relationship between different measures and facilitates the navigation through and interaction with complex and disparate sets of data.This paper introduces a toolkit developed for exploring complex biomedical data sets. The contributions of this paper are threefold: we suggest a modular design which facilitates the comparison and exploration of multiple data sets and visualization. We introduce a novel field data structure which allows interactive creation of new fields and we present boolean filters as a universal visualization tool.