Context
In Amira-Avizo, a surface or a volume can be colorized using different methods depending on the type of information to be displayed and the objective of the workflow.
The analysis tools and colormaps available in Amira-Avizo are very powerful and provide several ways to visually represent scalar values, labels, material properties, measurement results, or other computed information. Colormaps can be applied through the different module ports, such as Color Field or Colormap, and adjusted according to the data range and visualization requirements.
Therefore, the appropriate colorization method depends mainly on the type of data available and what needs to be communicated visually, for example, distinguishing segmented materials, displaying measurement values, highlighting intensity differences, or showing the results of a quantitative analysis.
For videos on colormap management, refer to the Xtras listed in the Related Links section at the end of this article.
A typical workflow may include the following steps:
Load the grayscale dataset, if required.
Generate or load a segmented object.
Create the corresponding visualization or display module.
Compute a quantity such as thickness, distance, curvature, or another scalar field.
Associate the resulting measurement data with the display module.
Select the corresponding scalar field as the coloring parameter.
Apply and adjust the colormap according to the range of values that should be highlighted.
For volume datasets, the same principle can be applied using modules such as Ortho Slice, Volume Rendering, or other volume visualization modules.
In practice, the choice of colorization method depends on the purpose of the visualization. A uniform color is sufficient when the objective is simply to identify an object. A scalar-based colormap is more suitable when the goal is to visualize measurement values, analysis results, or spatial variations across the data.
The following use cases illustrate some of the different colorization options available in Amira-Avizo.
1. Display a Volume Using Colorize by Measure
2. Display a Surface Using Label to Attribute
3. Display a Volume Using Label to Attribute
1. Display a Volume Using Colorize by Measure
1.1 Load the dataset:
<your installation folder>\data\tutorials\multicomp\cellbodies.labeledRegions.am.
1.2 Attach a Label Analysis module using the default settings. Click Apply to compute the available measurements. Among the computed values, BaryCenterX provides the X coordinate of the barycenter.
1.3 Attach a Colorize by Measure module to the analysis result.
1.4 Configure the Colorize by Measure parameters as follows:
1.4.1 Set Measure to BaryCenterX.
1.4.2 In Reference Colormap, click Edit and select Physicol.icol.am.
1.5 Attach an Axes module to cellbodies.labeledRegions.am.
1.6 Attach a Label Rendering module to the label dataset, then set its colormap to the Colormap-By-Measure result. The labeled volume is now colorized according to the selected measurement, in this case the X coordinate of the barycenter.
1.7 In the Colorize by Measure module, change the Measure port to Volume3d. Because auto-refresh is enabled for this module, the rendering is updated automatically, and the labels are now colorized according to their volume:
2. Display a Surface Using Label to Attribute
2.1 Load the datasets:
cellbodies.am and cellbodies.labels.am from <your installation folder>\data\tutorials\multicomp.
2.2 Generate and display the surface.
2.2.1 Attach a Generate Surface module to cellbodies.labels.am and click Apply. By default, the surface is generated with Smoothing = Unconstrained Smoothing. This means that the geometry of the generated surface can differ slightly from the original label boundaries. However, the reference volume remains unchanged because the Color Field values are computed from the label data.
This behavior is expected, and the workflow can be adjusted depending on the characteristics of the dataset.
2.2.2 Attach a Surface View module to display the generated surface.
2.3 Attach a Label Analysis module to cellbodies.labels.am. Select the Basic measures and click Apply.
2.4 Attach a Label to Attribute module to cellbodies.labels.Label-Analysis and compute the Volume3d attribute. This generates the dataset cellbodies.labels-Volume3d. In this dataset, each voxel belonging to an object contains an intensity value corresponding to the 3D volume of that object. For example, attaching a Volume Rendering module displays the result as follows:
2.5 Attach a Dilation module to cellbodies.labels-Volume3d and compute the dilated dataset, cellbodies.dilated.
2.6 Select the Surface View module created in step 2.2.2.
2.7 Expand the Data parameter category in the Properties panel.
2.8 Set Data > Color Field to cellbodies.dilated.
2.9 Set the colormap by clicking Colormap > Edit, then select physics.icol.am.
2.10 Check the minimum and maximum values of the Volume3d measure by selecting cellbodies.labels-Volume3d and reading the Data Info row. In this example, the range is [0.32, 7351].
2.11 Set the minimum and maximum values of the colormap to match the range of the measure. The surface is then pseudo-colored according to the Volume3d value computed for each labeled object.
The Dilation module described above is used to prepare the Color Field for reliable surface mapping. The Color Field is evaluated at the surface vertex positions. After surface smoothing, some vertices may no longer lie exactly within the voxels belonging to the original labeled object. As a result, a vertex may sample a neighboring or background voxel, which can lead to missing or incorrect color assignments, even though the surface still visually represents the same object.
To make the mapping more robust, it may be necessary to dilate the scalar field by one voxel before using it as the Color Field. This one-voxel dilation creates a small margin around each segmented object so that surface vertices displaced slightly by smoothing can still sample the correct scalar value.
The dilation does not modify the object volume calculated by Label Analysis. It is used only to improve the correspondence between the smoothed surface vertices and the voxel-based field used for visualization.
3. Display a Volume Using Label to Attribute
3.1 Generate a binary label field using any appropriate segmentation tool.
3.1.1 Load the dataset:
cellbodies.am from <your installation folder>\data\tutorials\multicomp.
3.1.2 Attach an Interactive Thresholding module and select the threshold to select the voxels of interest. For example, set Interactive Thresholding > Intensity Range to [62, 255].
3.1.3 Click Apply to generate the label image.
3.2 Attach a Label Analysis module to the label field. The set of Basic measures in 3D interpretation mode includes Volume3D.
3.3 Click Apply. The result includes a table and a new label field in which each connected region is uniquely labeled.
3.4 Attach the Label to Attribute module to the table cellbodies.Label-Analysis. Its Label Image port will automatically connects to the corresponding label field, cellbodies.label.
3.5 Set the Label to Attribute > Attribute port to Volume3D.
3.6 Click Apply. The module creates a new volume dataset by assigning to each voxel the Volume3D value associated with its label ID.
3.7 Display the cellbodies-Volume3d volume using the visualization module of your choice and select an appropriate colormap.
For example, the image below shows the result of applying this workflow to one of the cellbodies.am analysis examples, displayed using a Volume Rendering module and the physics.icol colormap.
Related Links
Knowledge Article: KA-01387 / How to Visualize Surface Distances.
For more information on colormap management, refer to the following Xtras:
The Xtra: Length Distribution Analysis demonstrates how to quantify the thickness distribution of a label along its length.