Recipe Description


The Cell Tracking recipe in Aivia detects cells and tracks their motility over time in fluorescence time-lapse microscopy images. The recipe measures the morphology, intensity and motion attributes of the detected cells for comprehensive characterization of cell migrations.

Parameters and Presets


Parameters

Parameters 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
Detection
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 objects
Detection
Fill Holes Size
0
5,000
Adjusts the maximum size threshold for filling in gaps inside a detected object; a lower value will preserve more holes in the detection
Detection
Smoothing Factor
0
100
Adjusts the amount of smoothing applied to the outline of the detected objects; a lower value will preserve more of the object's morphological features
Tracking
Object Size
0
50,000
Specifies the range of objects to be included in the analysis results based on the area of the detected objects
Tracking
Max Search Range
0
5,000
Specifies the maximum distance for track point match-making between successive time frames; a higher value will expand the search distance for fast-moving cells
Tracking
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
Tracking
Separation Factor
0
100
Adjusts the sensitivity of the object separation operation, a lower value will preserve larger objects with multiple intensity peaks

Presets


There are two preset groups in the recipe: Detection and Tracking; each group has three pre-configured parameter grouping 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)
5,898 (16-bit)
8 (8-bit)
1,966 (16-bit)
1 (8-bit)
262 (16-bit)
Fill Holes Size
10
25
50
Smoothing Factor
4
4
4

Tracking

Parameter Name
Low
Medium
High
Object Size
1 - 250
50 - 1,000
150 - 6,000
Max Search Range
20
20
20
Min Track Length
8
8
8
Separation Factor
50
70
85

Measurements


The Cell Tracking recipe generates morphological, intensity, and track measurements for each detected 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.
  • Morphological
    • Area
    • Circularity
  • Intensity (measured on the input channel)
    • Mean
    • Standard
    • Total
  • Track
    • Total Time
    • First Frame
    • Last Frame
    • X
    • Y
    • Acceleration Magnitude (Instantaneous)
    • Velocity Magnitude (Instantaneous)

Tutorial


Before beginning the tutorial, please download the Cell Tracking Demo Image (CellTrackDemo.zip). For information on how to select presets or modify parameter values, please refer to the tutorial on how to use the Recipe Console. You can download the image directly here.
  1. Unzip the demo file and load the demo image, CellTrackDemo.tif, into Aivia
  2. In the Recipe Console, click on the Recipe selection dropdown menu and select the Cell Tracking recipe
  3. Select the Medium presets for both the Detection and Tracking preset groups
  4. Click on the Show Advanced Interface icon showAdvOptions.PNG to expand the Recipe Console and show parameter options on the recipe
  5. Modify the parameter values in the recipe as follows while leaving the other values in tact
    • Smoothing Factor: 1
    • Object Size: 50 - 2000
    • Separation Factor: 57
  6. Click the From beginning button or press the F4 key on your keyboard to begin applying the recipe to the image

The detected objects outline and tracks will be overlaid on the image.

Results

Cell Tracking results

Image Credits


Chantal Brueggemann and Noelle L'Etoile, University of California - San Francisco