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The Neurite Outgrowth recipe in Aivia detects neurons and their neuronal processes (e.g. axons,

TheNeurite Outgrowth recipe in Aivia detects neurons and their neuronal processes (e.g., axons and dendrites) in 2D fluorescence microscopy images. The

This recipe also measures the morphology, intensity, and intensity count of the detected neurons as well as the length of the processes.

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On this page:

Table of Contents
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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

outline

outlines of the detected objects; a lower value will preserve more of the

object

objects'

s

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

area

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

Specifics

Specifies the typical width of neurites on the image; a lower value will

be more sensitive toward

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

. Each group has three pre-configured parameter

grouping

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

ThresholdIntensity

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

150 - 6,000Separation Factor507085

Neurite Detection

Parameter NameLowMediumHighBranch Sensitivity313846Mean Neurite Width2715Min Neurite Length0 1050

Measurements

The Neurite Outgrowth recipe generates morphological and intensity measurements for each detected neuron as well as a count of the total number of neurites per cell. You can add additional measurements to the analysis results by using the Measurement Tool in Aivia. The measurements generated by the recipe are as follows:

Measurement TypeMeasurement NameSomaNeuriteMorphologyLine LengthxxEnd Point CountxxBranch Point CountxxAreaxCircularityxComponent CountxxIntensityMeanxStandard DeviationxTotalx

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.

  1. Unzip the demo file and load the demo image, NeuriteOutgrowthDemo.tif, into Aivia
  2. In the Recipe Console, click on the Recipe selection dropdown menu and select the Neurite Outgrowth recipe
  3. Expand the Input and Output section in the recipe and make sure the input image is set to the green channel
  4. Select the High preset for the Detection group and the Medium preset for the Subset Filtering and Neurite Detection groups
  5. Click on the Show Advanced Interface icon Image Removed to expand the Recipe Console and show parameter options on the recipe
  6. Modify the parameter values in the recipe as follows while leaving the other values in tact
    • Contrast Threshold: 100
    • Separation Factor: 6
    • Branch Sensitivity: 54
    • Mean Neurite Width: 2.6
    • Min Neurite Length: 5
  7. Click the From beginning button or press the F4 key on your keyboard to begin applying the recipe to the image
The detected objects outlines will be overlaid on the image.

Results

Image Removed

Neurite Outgrowth results
Image credits

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.

  1. Unzip the demo file and load the demo image, “NeuriteOutgrowthDemo.tif,” into Aivia.

  2. In the Recipe Console, click on the Recipe selection dropdown menu and select the Neurite Outgrowth recipe.

  3. Expand the Input and Output section in the recipe and make sure the input image is set to the green channel.

  4. Select the High preset for the Detection group and the Medium preset for the Subset Filtering group.

  5. Click on the Show Advanced Interface icon to expand the Recipe Console and show parameter options for the recipe.

  6. 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

  7. Click the Start button or press the F4 key on your keyboard to begin applying the recipe to the image.

The detected object outlines will be overlaid on the image.


Image Added

Results

Image Added

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

  • Area

  • Circularity

  • Pixel-based Mean Intensity

  • Pixel-based Standard Deviation Intensity

  • Pixel-based Total Intensity

  • Component Count

  • Neurite Count

  • Cell Count

Neurite

None

None

  • Component Count

None

Image Credits

Ginger Withers, Whitman College, Cell Image Library (CIL:12566), http://www.cellimagelibrary.org/images/12566

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