We have developed a tool for the visualization of temporal changes of disease patterns, using stacks of medical images collected in time-series experiments. With this tool, users can generate 3D surface models representing disease patterns and observe changes over time in size, shape, and location of clinically significant image patterns. Statistical measurements of the volume of the observed disease patterns can be performed simultaneously. Spatial data integration occurs through the combination of 2D slices of an image stack into a 3D surface model. Temporal integration occurs through the sequential visualization of the 3D models from different time points. Visual integration enables the tool to show 2D images, 3D models and statistical d...
Visualization of large medical data sets requires advanced techniques in image processing and data ...
We propose and compare several methods for the visualization and exploration of time-varying volumet...
Efficient unsupervised algorithms for the detection of patterns in time series data, often called mo...
We have developed a tool for the visualization of temporal changes of disease patterns, using stacks...
In multiple sclerosis (MS), the amount of brain damage, anatomical location, shape, and changes are ...
Our perceptive of the scientific datasets has largely relied on numerical and statistical analysis o...
This paper describes a new three-dimensional interactive visualization supporting large scale medica...
This thesis investigates methods for the visualization of multi-field medical data. In the medical f...
We present the problem of visualizing time-varying medical data. Two medical imaging modalities are ...
Abstract. The simultaneous use of images obtained from different sources is common in medical diagno...
The increasing interest in time series data mining has had surprisingly little impact on real world ...
Visualization plays a vital role in the analysis of multimodal neuroimaging data. A major challenge ...
In this paper we consider how the use of Kaleidomaps can facilitate our understanding and interpreta...
The complexity and volume of collected medical data is greater now than at any point in the history ...
Abstract: Understanding complex biological systems requires data from manifold biological levels. Of...
Visualization of large medical data sets requires advanced techniques in image processing and data ...
We propose and compare several methods for the visualization and exploration of time-varying volumet...
Efficient unsupervised algorithms for the detection of patterns in time series data, often called mo...
We have developed a tool for the visualization of temporal changes of disease patterns, using stacks...
In multiple sclerosis (MS), the amount of brain damage, anatomical location, shape, and changes are ...
Our perceptive of the scientific datasets has largely relied on numerical and statistical analysis o...
This paper describes a new three-dimensional interactive visualization supporting large scale medica...
This thesis investigates methods for the visualization of multi-field medical data. In the medical f...
We present the problem of visualizing time-varying medical data. Two medical imaging modalities are ...
Abstract. The simultaneous use of images obtained from different sources is common in medical diagno...
The increasing interest in time series data mining has had surprisingly little impact on real world ...
Visualization plays a vital role in the analysis of multimodal neuroimaging data. A major challenge ...
In this paper we consider how the use of Kaleidomaps can facilitate our understanding and interpreta...
The complexity and volume of collected medical data is greater now than at any point in the history ...
Abstract: Understanding complex biological systems requires data from manifold biological levels. Of...
Visualization of large medical data sets requires advanced techniques in image processing and data ...
We propose and compare several methods for the visualization and exploration of time-varying volumet...
Efficient unsupervised algorithms for the detection of patterns in time series data, often called mo...