Parameters and Presets
Parameters
Recipe parameters for 3D Object Tracking and their descriptions are summarized in the table below.
Preset Group
Parameter Name
Min Value
Max Value
Description
Detection
Parameters and Presets
Parameters
Recipe parameters for 3D Object Tracking and their descriptions are summarized in the table below.
Preset Group | Parameter Name | Min Value | Max Value | Description |
---|---|---|---|---|
Detection | Image Smoothing Filter Size | 1 | 100 | Specifies the diameter of the filter that is used to smooth the input channel before further processing The available smoothing types are the following:
|
Average Object Radius (Remove Background only) | 0 | 1,000 (px or µm) | Specifies the radius of a typical object in the image for object enhancement and background removal; a lower value will preserve smaller objects | |
Min Edge Intensity | 0 | 255 (8-bit) 65,535 (16-bit) | Specifies the minimum object intensity that is typically found at the edge of the object for detection; when Remove Background is enabled, this parameter value is used to |
specify the minimum object intensity on the enhanced image; a lower value will detect bigger and more objects | ||||
Fill Holes Size | 0 | 1,000,000 (px2 or µm2) | Specifies the maximum size of gaps in detected objects that are filled; a lower value leads to the preservation of more holes in the detected objects | |
Partition | Object Radius | 0 | 1,000 (px or µm) | Specifies the range of objects to be included in the analysis results based on the radius of the detected objects |
Mesh Smoothing Factor | 0 | 10 | Adjusts the amount of smoothing applied to the surface reconstructions of the detected objects; a lower value will generate surfaces with greater similarity to the input image | |
Min Edge |
to |
Center Distance (Apply Partition only) | 0 | 1,000 (px or µm) | Specifies the minimum distance from the center of an object to the edge that is touching its closest neighboring object; this parameter is enabled only when Apply Partition is enabled; a lower value will apply object partitioning more aggressively, resulting in smaller, more uniform objects | |
Tracking | Minimum Track Length | 1 | 100 | 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 |
Maximum Search |
Distance | 0 | 1,000 (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 |
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 |
Track Lineage Option | Not applicable | Toggles tracking of object division and lineages | |
Matchmaking Option | Not applicable | Toggles the tracking algorithm used for track-point matchmaking between time points; the available options are Greedy Matching and Hungarian Matching |
Measurements
The 3D Object Tracking recipe generates morphological, intensity, and motility measurements for each detected 3D object as well as a count of the total number of 3D objects on the image. 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 in the table below.
Image Credits
Stegmaier J, Mikut R. (2017) Fuzzy-based propagation of prior knowledge to improve large-scale image analysis pipelines. PLoS One. 12(11):e0187535. doi:10.1371/journal.pone.0187535
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