Aivia Software

Particle Tracking

The Particle Tracking recipe in Aivia detects subcellular particles and tracks their motility over time in fluorescence time-lapse microscopy images.

This recipe measures intensity and motion attributes of the detected objects for comprehensive characterization of intracellular dynamics.

Parameters and Presets

Parameters

Recipe parameters for Particle Tracking and their descriptions are summarized in the table below.

Preset Group

Parameter Name

Min Value

Max Value

Description

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

Object Enhancement Factor

0

50

Adjusts the sensitivity of the bright peak enhancement operation; a lower value will enhance smaller, individual peaks

Contrast Threshold

0

255

Adjusts the detection sensitivity on the background-removed image; a lower value will detect more objects

Motion vs Intensity

Motion vs Intensity

0

10

Adjusts the relative weighting between motion and object intensity for track-point matchmaking between successive frames; a value of 5 will apply equal weights to motion and intensity for matchmaking

Tracking

Gap Length

0

10

Specifies the maximum number of time frames for linking tracks that are spatially colocated; a higher value will preserve particle tracks for longer

Min Track Length

0

50,000

Specifies the minimum number of time frames before a detected object is considered a valid track; a lower value will generate more, and often shorter, tracks

Max Search Range

0

50,000 px or µm

Specifies the maximum distance for track-point matchmaking between successive time frames; a higher value will expand the search distance for fast-moving cells

 

Presets

There are three preset groups in the recipe: Detection, Motion vs Intensity, and Tracking. Each group has three pre-configured parameter groupings to help you get started on the analysis. The default preset values are in the subsections to follow.

 

Detection

Parameter Name

Low

Medium

High

Background Removal Factor

75

75

75

Object Enhancement Factor

2

2

2

Contrast Threshold

125

65

15



 

Motion vs Intensity

Parameter Name

Motion

Mixed

Intensity

Parameter Name

Motion

Mixed

Intensity

Motion vs Intensity

0

5

10

 

 

Tracking

Parameter Name

Low

Medium

High

Gap Length

5

5

5

Min Track Length

3

3

3

Max Search Range

5 px or µm

5 px or µm

65 px or µm



 

Tutorial (written steps)

Before beginning the tutorial, please download the Particle Tracking 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, “ParticleTrackDemo.tif,” into Aivia.

  2. In the Recipe Console, click on the Recipe selection dropdown menu and select the Particle Tracking recipe.

  3. Select the following presets for each preset group:

    • Detection: Medium

    • Motion vs Intensity: Motion

    • Tracking: Low

  4. Click on the caret to the left of the Tracking preset group to show the preset parameters.

  5. Modify the parameter value as follows, leaving the other parameters intact:

    • Max Search Range: 0.7

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

The detected particle tracks will be overlaid on the image.

 

 

Particle Tracking Tutorial Results


Tutorial (video)

 

Video: Particle Tracking Recipe Tutorial Worked Example (54s)

 

Measurements

The Particle Tracking recipe generates intensity and position measurements for each detected particle. You can add additional measurements to the analysis results with the Measurement Tool in Aivia and explore measurement definitions on the Measurement Definitions page. The measurements generated by the recipe are in the table below.

Intensity

Position

  • Pixel-based Mean Intensity

  • Pixel-based Total Intensity

  • Pixel-based Standard Deviation Intensity

  • Total Time

  • First Frame

  • Last Frame

  • Centroid X

  • Centroid Y

  • Velocity Magnitude

 

 

Image Credits

Laura Anne Lowery, Boston College, Boston MA; David Van Vactor, Harvard Medical School, Boston MA