Aivia Software
Neurite Outgrowth
The Neurite Outgrowth recipe in Aivia detects neurons and their neuronal processes (e.g., axons and dendrites) in 2D fluorescence microscopy images.
This recipe also measures the morphology, intensity, and count of the detected neurons.
On this page:
Parameters and Presets
Parameters
Recipe parameters for Neurite Outgrowth and their descriptions are summarized in the table below.
Preset Group | Parameter Name | Min Value | Max Value | Description |
|---|---|---|---|---|
Detection | Background Removal Factor | 0 | 100 | Adjusts the sensitivity of the background removal operation; a lower value will preserve larger objects and more background variations |
Contrast Threshold | 0 | 255 (8-bit) 65,535 (16-bit) | Adjusts the detection sensitivity on the background-removed image; a lower value will detect bigger and more cell bodies | |
Fill Holes Size | 0 | 5,000 px2 or µm2 | Adjusts the maximum size threshold for filling in gaps inside a detected object; a lower value will preserve more holes in the detection | |
Smoothing Factor | 0 | 100 | Adjusts the amount of smoothing applied to the outlines of the detected objects; a lower value will preserve more of the objects' morphological features | |
Subset Filtering | Object Size | 0 | 1,000,000 px2 or µm2 | Specifies the range of objects to be included in the analysis results based on the areas of the detected objects |
Separation Factor (Cell Partition only) | 0 | 100 | Adjusts the sensitivity of the object separation operation; a lower value will preserve larger objects with multiple intensity peaks | |
Neurite Detection | Branch Sensitivity | 1 | 100 | Adjusts the sensitivity of the neurite tracing operation; a lower value will result in detection of fewer short branches |
Mean Neurite Width | 0.1 px or µm | 100 px or µm | Specifies the typical width of neurites on the image; a lower value will result in higher sensitivity for detection of thinner neurites | |
Min Neurite Length | 0 | 1,000 px or µm | Specifies the minimum length of neurite branches to be included in the analysis result |
Presets
There are three preset groups in the recipe: Detection, Subset Filtering and Neurite Detection. Each group has three pre-configured parameter groupings to help you get started on the analysis. The default preset values are as follows:
Detection
Parameter Name | Low | Medium | High |
|---|---|---|---|
Background Removal Factor | 25 | 55 | 75 |
Contrast Threshold | 23 (8-bit) | 8 (8-bit) | 1 (8-bit) |
5,898 (16-bit) | 1,966 (16-bit) | 262 (16-bit) | |
Fill Holes Size | 10 px2 or µm2 | 25 px2 or µm2 | 50 px2 or µm2 |
Smoothing Factor | 4 | 4 | 4 |
Subset Filtering
Parameter Name | Small | Medium | Large |
|---|---|---|---|
Object Size | 1 - 250 px2 or µm2 | 50 - 1,000 px2 or µm2 | 150 - 6,000 px2 or µm2 |
Separation Factor | 50 | 70 | 85 |
Neurite Detection
Parameter Name | Low | Medium | High |
|---|---|---|---|
Branch Sensitivity | 31 | 38 | 46 |
Mean Neurite Width | 2 px or µm | 7 px or µm | 15 px or µm |
Min Neurite Length | 0 px or µm | 10 px or µm | 50 px or µm |
Tutorial
Before beginning the tutorial, please download the Neurite Outgrowth Demo image. For information on how to select presets or modify parameter values, please refer to the tutorial on how to use the Recipe Console.
Unzip the demo file and load the demo image, “NeuriteOutgrowthDemo.tif,” into Aivia.
In the Recipe Console, click on the Recipe selection dropdown menu and select the Neurite Outgrowth recipe.
Expand the Input and Output section in the recipe and make sure the input image is set to the green channel.
Select the High preset for the Detection group and the Medium preset for the Subset Filtering group.
Click on the Show Advanced Interface icon to expand the Recipe Console and show parameter options for the recipe.
Modify the parameter values in the recipe as follows while leaving the other values intact:
Contrast Threshold: 100
Branch Sensitivity: 54
Mean Neurite Width: 2.6
Min Neurite Length: 5
Click the Start button or press the
F4key on your keyboard to begin applying the recipe to the image.
The detected object outlines will be overlaid on the image.
Results
Measurements
The Neurite Outgrowth recipe generates morphological, intensity, and count measurements for each detected neuron, including the total number of neurites per cell. You can add additional measurements to the analysis results with the Measurement Tool in Aivia and view measurement definitions on the Measurement Definitions page. The measurements generated by the recipe are given in the table below.
Object Set | Morphology | Intensity | Count | Advanced |
|---|---|---|---|---|
Soma |
|
|
|
|
Neurite | None | None |
| None |
Image Credits
Ginger Withers, Whitman College, Cell Image Library (CIL:12566), http://www.cellimagelibrary.org/images/12566